{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/machine-translation/papers/2","list_of":"/task/machine-translation","task":"Machine Translation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":2,"pages_in_order":108,"rows_per_page":100,"rows":[101,200],"of":10752,"counts":{"archive_papers_tagged":10752,"with_a_code_link":2444,"where_syntology_ran_a_sample":477,"not_listed_spam_title":0,"listed":10752,"listed_where_code_ran":477,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":381,"every_run_a_failure_of_syntologys_instrument":96,"listed_with_a_run_with_no_instrument_failure":381,"listed_every_run_a_failure_of_syntologys_instrument":96,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/machine-translation","prev":"/task/machine-translation","next":"/task/machine-translation/papers/3","papers":[{"url":"/paper/memory-efficient-adaptive-optimization-for","slug":"memory-efficient-adaptive-optimization-for","title":"Memory-Efficient Adaptive Optimization","date":"2019-01-30","arxiv_id":"1901.11150","repositories_listed":4,"syntology":null},{"url":"/paper/texar-a-modularized-versatile-and-extensible-1","slug":"texar-a-modularized-versatile-and-extensible-1","title":"Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation","date":"2018-09-04","arxiv_id":"1809.00794","repositories_listed":4,"syntology":{"n":12,"n_ran":11,"n_constructed":0,"n_ran_checked":11,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/texar-a-modularized-versatile-and-extensible-1#ran","syntology_url":"https://syntology.ai/paper/1809.00794","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1809.00794"}},"official":{"repos":["asyml/texar"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/training-tips-for-the-transformer-model","slug":"training-tips-for-the-transformer-model","title":"Training Tips for the Transformer Model","date":"2018-04-01","arxiv_id":"1804.00247","repositories_listed":4,"syntology":null},{"url":"/paper/deep-k-nearest-neighbors-towards-confident","slug":"deep-k-nearest-neighbors-towards-confident","title":"Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning","date":"2018-03-13","arxiv_id":"1803.04765","repositories_listed":4,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deep-k-nearest-neighbors-towards-confident#ran","syntology_url":"https://syntology.ai/paper/1803.04765","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1803.04765"}},"official":null}},{"url":"/paper/multimodal-generative-models-for-scalable","slug":"multimodal-generative-models-for-scalable","title":"Multimodal Generative Models for Scalable Weakly-Supervised Learning","date":"2018-02-14","arxiv_id":"1802.05335","repositories_listed":4,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/multimodal-generative-models-for-scalable#ran","syntology_url":"https://syntology.ai/paper/1802.05335","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1802.05335"}},"official":null}},{"url":"/paper/improving-lexical-choice-in-neural-machine","slug":"improving-lexical-choice-in-neural-machine","title":"Improving Lexical Choice in Neural Machine Translation","date":"2017-10-03","arxiv_id":"1710.01329","repositories_listed":4,"syntology":{"n":9,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/improving-lexical-choice-in-neural-machine#ran","syntology_url":"https://syntology.ai/paper/1710.01329","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1710.01329"}},"official":{"repos":["tnq177/improving_lexical_choice_in_nmt"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/towards-neural-phrase-based-machine","slug":"towards-neural-phrase-based-machine","title":"Towards Neural Phrase-based Machine Translation","date":"2017-06-17","arxiv_id":"1706.05565","repositories_listed":4,"syntology":null},{"url":"/paper/learning-to-skim-text","slug":"learning-to-skim-text","title":"Learning to Skim Text","date":"2017-04-23","arxiv_id":"1704.06877","repositories_listed":4,"syntology":null},{"url":"/paper/nematus-a-toolkit-for-neural-machine","slug":"nematus-a-toolkit-for-neural-machine","title":"Nematus: a Toolkit for Neural Machine Translation","date":"2017-03-13","arxiv_id":"1703.04357","repositories_listed":4,"syntology":null},{"url":"/paper/outrageously-large-neural-networks-the","slug":"outrageously-large-neural-networks-the","title":"Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer","date":"2017-01-23","arxiv_id":"1701.06538","repositories_listed":4,"syntology":{"n":6,"n_ran":4,"n_constructed":4,"n_ran_checked":4,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":6,"phrase":"4 ran (of which 4 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified; every one of the 4 samples that ran constructed an object rather than computing a result","sample_list":"/paper/outrageously-large-neural-networks-the#ran","syntology_url":"https://syntology.ai/paper/1701.06538","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1701.06538"}},"official":null}},{"url":"/paper/opennmt-open-source-toolkit-for-neural","slug":"opennmt-open-source-toolkit-for-neural","title":"OpenNMT: Open-Source Toolkit for Neural Machine Translation","date":"2017-01-10","arxiv_id":"1701.02810","repositories_listed":4,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"0 ran · 1 unverified","sample_list":"/paper/opennmt-open-source-toolkit-for-neural#ran","syntology_url":"https://syntology.ai/paper/1701.02810","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1701.02810"}},"official":{"repos":["OpenNMT/OpenNMT"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"url":"/paper/registering-source-tokens-to-target-language","slug":"registering-source-tokens-to-target-language","title":"Registering Source Tokens to Target Language Spaces in Multilingual Neural Machine Translation","date":"2025-01-06","arxiv_id":"2501.02979","repositories_listed":3,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/registering-source-tokens-to-target-language#ran","syntology_url":"https://syntology.ai/paper/2501.02979","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2501.02979"}},"official":{"repos":["zhiqu22/mitre","huggingface.co/naist-nlp/mitre_466m","huggingface.co/naist-nlp/mitre_913m"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/ladder-a-model-agnostic-framework-boosting","slug":"ladder-a-model-agnostic-framework-boosting","title":"Ladder: A Model-Agnostic Framework Boosting LLM-based Machine Translation to the Next Level","date":"2024-06-22","arxiv_id":"2406.15741","repositories_listed":3,"syntology":{"n":8,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":8,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/ladder-a-model-agnostic-framework-boosting#ran","syntology_url":"https://syntology.ai/paper/2406.15741","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.15741"}},"official":{"repos":["fzp0424/ladder","fzp0424/mt-ladder"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/knowledge-fusion-of-large-language-models","slug":"knowledge-fusion-of-large-language-models","title":"Knowledge Fusion of Large Language Models","date":"2024-01-19","arxiv_id":"2401.10491","repositories_listed":3,"syntology":{"n":4,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":4,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/knowledge-fusion-of-large-language-models#ran","syntology_url":"https://syntology.ai/paper/2401.10491","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.10491"}},"official":{"repos":["fanqiwan/fusellm"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/ai-driven-platform-for-systematic","slug":"ai-driven-platform-for-systematic","title":"ShennongAlpha: an AI-driven sharing and collaboration platform for intelligent curation, acquisition, and translation of natural medicinal material knowledge","date":"2023-12-27","arxiv_id":"2401.00020","repositories_listed":3,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/ai-driven-platform-for-systematic#ran","syntology_url":"https://syntology.ai/paper/2401.00020","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.00020"}},"official":{"repos":["shennong-program/pycgs","shennong-program/shennongname","shennong-program/mlmd"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/medgen-a-python-natural-language-processing","slug":"medgen-a-python-natural-language-processing","title":"Ascle: A Python Natural Language Processing Toolkit for Medical Text Generation","date":"2023-11-28","arxiv_id":"2311.16588","repositories_listed":3,"syntology":null},{"url":"/paper/xcomet-transparent-machine-translation","slug":"xcomet-transparent-machine-translation","title":"xCOMET: Transparent Machine Translation Evaluation through Fine-grained Error Detection","date":"2023-10-16","arxiv_id":"2310.10482","repositories_listed":3,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":1,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/xcomet-transparent-machine-translation#ran","syntology_url":"https://syntology.ai/paper/2310.10482","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.10482"}},"official":null}},{"url":"/paper/accelerating-transformer-inference-for","slug":"accelerating-transformer-inference-for","title":"Accelerating Transformer Inference for Translation via Parallel Decoding","date":"2023-05-17","arxiv_id":"2305.10427","repositories_listed":3,"syntology":{"n":10,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/accelerating-transformer-inference-for#ran","syntology_url":"https://syntology.ai/paper/2305.10427","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.10427"}},"official":{"repos":["teelinsan/parallel-decoding"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/openicl-an-open-source-framework-for-in","slug":"openicl-an-open-source-framework-for-in","title":"OpenICL: An Open-Source Framework for In-context Learning","date":"2023-03-06","arxiv_id":"2303.02913","repositories_listed":3,"syntology":null},{"url":"/paper/small-100-introducing-shallow-multilingual","slug":"small-100-introducing-shallow-multilingual","title":"SMaLL-100: Introducing Shallow Multilingual Machine Translation Model for Low-Resource Languages","date":"2022-10-20","arxiv_id":"2210.11621","repositories_listed":3,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/small-100-introducing-shallow-multilingual#ran","syntology_url":"https://syntology.ai/paper/2210.11621","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2210.11621"}},"official":{"repos":["alirezamshi/small100"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/towards-robust-k-nearest-neighbor-machine","slug":"towards-robust-k-nearest-neighbor-machine","title":"Towards Robust k-Nearest-Neighbor Machine Translation","date":"2022-10-17","arxiv_id":"2210.08808","repositories_listed":3,"syntology":null},{"url":"/paper/preparing-an-endangered-language-for-the","slug":"preparing-an-endangered-language-for-the","title":"Preparing an Endangered Language for the Digital Age: The Case of Judeo-Spanish","date":"2022-05-31","arxiv_id":"2205.15599","repositories_listed":3,"syntology":null},{"url":"/paper/multilingual-machine-translation-with-hyper","slug":"multilingual-machine-translation-with-hyper","title":"Multilingual Machine Translation with Hyper-Adapters","date":"2022-05-22","arxiv_id":"2205.10835","repositories_listed":3,"syntology":null},{"url":"/paper/8-bit-optimizers-via-block-wise-quantization","slug":"8-bit-optimizers-via-block-wise-quantization","title":"8-bit Optimizers via Block-wise Quantization","date":"2021-10-06","arxiv_id":"2110.02861","repositories_listed":3,"syntology":null},{"url":"/paper/indicbart-a-pre-trained-model-for-natural","slug":"indicbart-a-pre-trained-model-for-natural","title":"IndicBART: A Pre-trained Model for Indic Natural Language Generation","date":"2021-09-07","arxiv_id":"2109.02903","repositories_listed":3,"syntology":null},{"url":"/paper/shifts-a-dataset-of-real-distributional-shift","slug":"shifts-a-dataset-of-real-distributional-shift","title":"Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks","date":"2021-07-15","arxiv_id":"2107.07455","repositories_listed":3,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/shifts-a-dataset-of-real-distributional-shift#ran","syntology_url":"https://syntology.ai/paper/2107.07455","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.07455"}},"official":{"repos":["yandex-research/shifts"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/power-law-graph-transformer-for-machine","slug":"power-law-graph-transformer-for-machine","title":"Power Law Graph Transformer for Machine Translation and Representation Learning","date":"2021-06-27","arxiv_id":"2107.02039","repositories_listed":3,"syntology":null},{"url":"/paper/bartscore-evaluating-generated-text-as-text","slug":"bartscore-evaluating-generated-text-as-text","title":"BARTScore: Evaluating Generated Text as Text Generation","date":"2021-06-22","arxiv_id":"2106.11520","repositories_listed":3,"syntology":null},{"url":"/paper/adaptive-nearest-neighbor-machine-translation","slug":"adaptive-nearest-neighbor-machine-translation","title":"Adaptive Nearest Neighbor Machine Translation","date":"2021-05-27","arxiv_id":"2105.13022","repositories_listed":3,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/adaptive-nearest-neighbor-machine-translation#ran","syntology_url":"https://syntology.ai/paper/2105.13022","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.13022"}},"official":{"repos":["zhengxxn/adaptive-knn-mt"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/contrastive-learning-for-many-to-many","slug":"contrastive-learning-for-many-to-many","title":"Contrastive Learning for Many-to-many Multilingual Neural Machine Translation","date":"2021-05-20","arxiv_id":"2105.09501","repositories_listed":3,"syntology":null},{"url":"/paper/experts-errors-and-context-a-large-scale","slug":"experts-errors-and-context-a-large-scale","title":"Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation","date":"2021-04-29","arxiv_id":"2104.14478","repositories_listed":3,"syntology":null},{"url":"/paper/sparse-attention-with-linear-units","slug":"sparse-attention-with-linear-units","title":"Sparse Attention with Linear Units","date":"2021-04-14","arxiv_id":"2104.07012","repositories_listed":3,"syntology":{"n":5,"n_ran":3,"n_constructed":1,"n_ran_checked":3,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 1 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/sparse-attention-with-linear-units#ran","syntology_url":"https://syntology.ai/paper/2104.07012","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.07012"}},"official":{"repos":["bzhangGo/zero"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["listed"]}}},{"url":"/paper/fudge-controlled-text-generation-with-future","slug":"fudge-controlled-text-generation-with-future","title":"FUDGE: Controlled Text Generation With Future Discriminators","date":"2021-04-12","arxiv_id":"2104.05218","repositories_listed":3,"syntology":{"n":4,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/fudge-controlled-text-generation-with-future#ran","syntology_url":"https://syntology.ai/paper/2104.05218","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.05218"}},"official":{"repos":["yangkevin2/naacl-2021-fudge-controlled-generation"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["listed"]}}},{"url":"/paper/beyond-fully-connected-layers-with","slug":"beyond-fully-connected-layers-with","title":"Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters","date":"2021-02-17","arxiv_id":"2102.08597","repositories_listed":3,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"0 ran · 1 unverified","sample_list":"/paper/beyond-fully-connected-layers-with#ran","syntology_url":"https://syntology.ai/paper/2102.08597","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2102.08597"}},"official":{"repos":["astonzhang/Parameterization-of-Hypercomplex-Multiplications"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"url":"/paper/xor-qa-cross-lingual-open-retrieval-question","slug":"xor-qa-cross-lingual-open-retrieval-question","title":"XOR QA: Cross-lingual Open-Retrieval Question Answering","date":"2020-10-22","arxiv_id":"2010.11856","repositories_listed":3,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":6,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":2,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/xor-qa-cross-lingual-open-retrieval-question#ran","syntology_url":"https://syntology.ai/paper/2010.11856","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.11856"}},"official":{"repos":["AkariAsai/XORQA"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/end-to-end-slot-alignment-and-recognition-for","slug":"end-to-end-slot-alignment-and-recognition-for","title":"End-to-End Slot Alignment and Recognition for Cross-Lingual NLU","date":"2020-04-29","arxiv_id":"2004.14353","repositories_listed":3,"syntology":null},{"url":"/paper/improving-massively-multilingual-neural","slug":"improving-massively-multilingual-neural","title":"Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation","date":"2020-04-24","arxiv_id":"2004.11867","repositories_listed":3,"syntology":{"n":13,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":11,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 11 unverified","sample_list":"/paper/improving-massively-multilingual-neural#ran","syntology_url":"https://syntology.ai/paper/2004.11867","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.11867"}},"official":{"repos":["EdinburghNLP/opus-100-corpus","bzhangGo/zero"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":11,"ran_from_kinds":["official"]}}},{"url":"/paper/simalign-high-quality-word-alignments-without","slug":"simalign-high-quality-word-alignments-without","title":"SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings","date":"2020-04-18","arxiv_id":"2004.08728","repositories_listed":3,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/simalign-high-quality-word-alignments-without#ran","syntology_url":"https://syntology.ai/paper/2004.08728","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.08728"}},"official":{"repos":["masoudjs/simalign"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/felix-flexible-text-editing-through-tagging","slug":"felix-flexible-text-editing-through-tagging","title":"Felix: Flexible Text Editing Through Tagging and Insertion","date":"2020-03-24","arxiv_id":"2003.10687","repositories_listed":3,"syntology":{"n":5,"n_ran":3,"n_constructed":3,"n_ran_checked":3,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":1,"phrase":"3 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","sample_list":"/paper/felix-flexible-text-editing-through-tagging#ran","syntology_url":"https://syntology.ai/paper/2003.10687","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.10687"}},"official":{"repos":["google-research/google-research"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/incorporating-bert-into-neural-machine-1","slug":"incorporating-bert-into-neural-machine-1","title":"Incorporating BERT into Neural Machine Translation","date":"2020-02-17","arxiv_id":"2002.06823","repositories_listed":3,"syntology":null},{"url":"/paper/amr-similarity-metrics-from-principles","slug":"amr-similarity-metrics-from-principles","title":"AMR Similarity Metrics from Principles","date":"2020-01-29","arxiv_id":"2001.10929","repositories_listed":3,"syntology":null},{"url":"/paper/muse-parallel-multi-scale-attention-for","slug":"muse-parallel-multi-scale-attention-for","title":"MUSE: Parallel Multi-Scale Attention for Sequence to Sequence Learning","date":"2019-11-17","arxiv_id":"1911.09483","repositories_listed":3,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"0 ran · 1 unverified","sample_list":"/paper/muse-parallel-multi-scale-attention-for#ran","syntology_url":"https://syntology.ai/paper/1911.09483","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.09483"}},"official":{"repos":["lancopku/MUSE"],"state":"official: not harvested","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":[]}}},{"url":"/paper/non-intrusive-load-monitoring-with-an","slug":"non-intrusive-load-monitoring-with-an","title":"Improving Non-Intrusive Load Disaggregation through an Attention-Based Deep Neural Network","date":"2019-11-15","arxiv_id":"1912.00759","repositories_listed":3,"syntology":null},{"url":"/paper/personalizing-graph-neural-networks-with","slug":"personalizing-graph-neural-networks-with","title":"Personalized Graph Neural Networks with Attention Mechanism for Session-Aware Recommendation","date":"2019-10-20","arxiv_id":"1910.08887","repositories_listed":3,"syntology":null},{"url":"/paper/monotonic-multihead-attention-1","slug":"monotonic-multihead-attention-1","title":"Monotonic Multihead Attention","date":"2019-09-26","arxiv_id":"1909.12406","repositories_listed":3,"syntology":null},{"url":"/paper/ludwig-a-type-based-declarative-deep-learning","slug":"ludwig-a-type-based-declarative-deep-learning","title":"Ludwig: a type-based declarative deep learning toolbox","date":"2019-09-17","arxiv_id":"1909.07930","repositories_listed":3,"syntology":null},{"url":"/paper/adaptively-sparse-transformers","slug":"adaptively-sparse-transformers","title":"Adaptively Sparse Transformers","date":"2019-08-30","arxiv_id":"1909.00015","repositories_listed":3,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/adaptively-sparse-transformers#ran","syntology_url":"https://syntology.ai/paper/1909.00015","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.00015"}},"official":{"repos":["deep-spin/entmax"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/levenshtein-transformer","slug":"levenshtein-transformer","title":"Levenshtein Transformer","date":"2019-05-27","arxiv_id":"1905.11006","repositories_listed":3,"syntology":null},{"url":"/paper/the-evolved-transformer","slug":"the-evolved-transformer","title":"The Evolved Transformer","date":"2019-01-30","arxiv_id":"1901.11117","repositories_listed":3,"syntology":null},{"url":"/paper/pay-less-attention-with-lightweight-and","slug":"pay-less-attention-with-lightweight-and","title":"Pay Less Attention with Lightweight and Dynamic Convolutions","date":"2019-01-29","arxiv_id":"1901.10430","repositories_listed":3,"syntology":null},{"url":"/paper/stochastic-gradient-push-for-distributed-deep","slug":"stochastic-gradient-push-for-distributed-deep","title":"Stochastic Gradient Push for Distributed Deep Learning","date":"2018-11-27","arxiv_id":"1811.10792","repositories_listed":3,"syntology":{"n":15,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":5,"n_honours":1,"n_violates":0,"n_no_contract":9,"n_pointer_only":2,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 1 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/stochastic-gradient-push-for-distributed-deep#ran","syntology_url":"https://syntology.ai/paper/1811.10792","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1811.10792"}},"official":null}},{"url":"/paper/simplifying-neural-machine-translation-with","slug":"simplifying-neural-machine-translation-with","title":"Simplifying Neural Machine Translation with Addition-Subtraction Twin-Gated Recurrent Networks","date":"2018-10-30","arxiv_id":"1810.12546","repositories_listed":3,"syntology":null},{"url":"/paper/unsupervised-statistical-machine-translation","slug":"unsupervised-statistical-machine-translation","title":"Unsupervised Statistical Machine Translation","date":"2018-09-04","arxiv_id":"1809.01272","repositories_listed":3,"syntology":null},{"url":"/paper/understanding-back-translation-at-scale","slug":"understanding-back-translation-at-scale","title":"Understanding Back-Translation at Scale","date":"2018-08-28","arxiv_id":"1808.09381","repositories_listed":3,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/understanding-back-translation-at-scale#ran","syntology_url":"https://syntology.ai/paper/1808.09381","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1808.09381"}},"official":{"repos":["pytorch/fairseq"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/sentencepiece-a-simple-and-language-1","slug":"sentencepiece-a-simple-and-language-1","title":"SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing","date":"2018-08-19","arxiv_id":"1808.06226","repositories_listed":3,"syntology":null},{"url":"/paper/pervasive-attention-2d-convolutional-neural-1","slug":"pervasive-attention-2d-convolutional-neural-1","title":"Pervasive Attention: 2D Convolutional Neural Networks for Sequence-to-Sequence Prediction","date":"2018-08-11","arxiv_id":"1808.03867","repositories_listed":3,"syntology":null},{"url":"/paper/on-adversarial-examples-for-character-level","slug":"on-adversarial-examples-for-character-level","title":"On Adversarial Examples for Character-Level Neural Machine Translation","date":"2018-06-23","arxiv_id":"1806.09030","repositories_listed":3,"syntology":null},{"url":"/paper/mixed-precision-training-for-nlp-and-speech","slug":"mixed-precision-training-for-nlp-and-speech","title":"Mixed-Precision Training for NLP and Speech Recognition with OpenSeq2Seq","date":"2018-05-25","arxiv_id":"1805.10387","repositories_listed":3,"syntology":null},{"url":"/paper/deep-reinforcement-learning-for-sequence-to","slug":"deep-reinforcement-learning-for-sequence-to","title":"Deep Reinforcement Learning For Sequence to Sequence Models","date":"2018-05-24","arxiv_id":"1805.09461","repositories_listed":3,"syntology":{"n":17,"n_ran":16,"n_constructed":0,"n_ran_checked":15,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":15,"n_pointer_only":2,"phrase":"16 ran (of which 0 constructed an object rather than computing a result; 15 with no instrument failure: 0 honoured, 0 violated, 15 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/deep-reinforcement-learning-for-sequence-to#ran","syntology_url":"https://syntology.ai/paper/1805.09461","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1805.09461"}},"official":{"repos":["yaserkl/RLSeq2Seq"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/the-best-of-both-worlds-combining-recent","slug":"the-best-of-both-worlds-combining-recent","title":"The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation","date":"2018-04-26","arxiv_id":"1804.09849","repositories_listed":3,"syntology":null},{"url":"/paper/marian-fast-neural-machine-translation-in-c","slug":"marian-fast-neural-machine-translation-in-c","title":"Marian: Fast Neural Machine Translation in C++","date":"2018-04-01","arxiv_id":"1804.00344","repositories_listed":3,"syntology":null},{"url":"/paper/synthetic-and-natural-noise-both-break-neural","slug":"synthetic-and-natural-noise-both-break-neural","title":"Synthetic and Natural Noise Both Break Neural Machine Translation","date":"2017-11-06","arxiv_id":"1711.02173","repositories_listed":3,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/synthetic-and-natural-noise-both-break-neural#ran","syntology_url":"https://syntology.ai/paper/1711.02173","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1711.02173"}},"official":{"repos":["ybisk/charNMT-noise"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/compressing-word-embeddings-via-deep","slug":"compressing-word-embeddings-via-deep","title":"Compressing Word Embeddings via Deep Compositional Code Learning","date":"2017-11-03","arxiv_id":"1711.01068","repositories_listed":3,"syntology":null},{"url":"/paper/confidence-through-attention","slug":"confidence-through-attention","title":"Confidence through Attention","date":"2017-10-10","arxiv_id":"1710.03743","repositories_listed":3,"syntology":null},{"url":"/paper/semeval-2017-task-1-semantic-textual","slug":"semeval-2017-task-1-semantic-textual","title":"SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation","date":"2017-07-31","arxiv_id":"1708.00055","repositories_listed":3,"syntology":null},{"url":"/paper/deep-architectures-for-neural-machine","slug":"deep-architectures-for-neural-machine","title":"Deep Architectures for Neural Machine Translation","date":"2017-07-24","arxiv_id":"1707.07631","repositories_listed":3,"syntology":null},{"url":"/paper/relevance-of-unsupervised-metrics-in-task","slug":"relevance-of-unsupervised-metrics-in-task","title":"Relevance of Unsupervised Metrics in Task-Oriented Dialogue for Evaluating Natural Language Generation","date":"2017-06-29","arxiv_id":"1706.09799","repositories_listed":3,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/relevance-of-unsupervised-metrics-in-task#ran","syntology_url":"https://syntology.ai/paper/1706.09799","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1706.09799"}},"official":{"repos":["Maluuba/nlg-eval"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/a-regularized-framework-for-sparse-and","slug":"a-regularized-framework-for-sparse-and","title":"A Regularized Framework for Sparse and Structured Neural Attention","date":"2017-05-22","arxiv_id":"1705.07704","repositories_listed":3,"syntology":null},{"url":"/paper/improving-neural-machine-translation-with","slug":"improving-neural-machine-translation-with","title":"Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets","date":"2017-03-15","arxiv_id":"1703.04887","repositories_listed":3,"syntology":{"n":6,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/improving-neural-machine-translation-with#ran","syntology_url":"https://syntology.ai/paper/1703.04887","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1703.04887"}},"official":{"repos":["ZhenYangIACAS/NMT_GAN"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/atr4s-toolkit-with-state-of-the-art-automatic","slug":"atr4s-toolkit-with-state-of-the-art-automatic","title":"ATR4S: Toolkit with State-of-the-art Automatic Terms Recognition Methods in Scala","date":"2016-11-23","arxiv_id":"1611.07804","repositories_listed":3,"syntology":null},{"url":"/paper/an-actor-critic-algorithm-for-sequence","slug":"an-actor-critic-algorithm-for-sequence","title":"An Actor-Critic Algorithm for Sequence Prediction","date":"2016-07-24","arxiv_id":"1607.07086","repositories_listed":3,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"0 ran · 1 unverified","sample_list":"/paper/an-actor-critic-algorithm-for-sequence#ran","syntology_url":"https://syntology.ai/paper/1607.07086","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1607.07086"}},"official":{"repos":["rizar/actor-critic-public"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"url":"/paper/neural-semantic-encoders","slug":"neural-semantic-encoders","title":"Neural Semantic Encoders","date":"2016-07-14","arxiv_id":"1607.04315","repositories_listed":3,"syntology":null},{"url":"/paper/achieving-open-vocabulary-neural-machine","slug":"achieving-open-vocabulary-neural-machine","title":"Achieving Open Vocabulary Neural Machine Translation with Hybrid Word-Character Models","date":"2016-04-04","arxiv_id":"1604.00788","repositories_listed":3,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/achieving-open-vocabulary-neural-machine#ran","syntology_url":"https://syntology.ai/paper/1604.00788","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1604.00788"}},"official":null}},{"url":"/paper/neural-language-correction-with-character","slug":"neural-language-correction-with-character","title":"Neural Language Correction with Character-Based Attention","date":"2016-03-31","arxiv_id":"1603.09727","repositories_listed":3,"syntology":null},{"url":"/paper/modeling-coverage-for-neural-machine","slug":"modeling-coverage-for-neural-machine","title":"Modeling Coverage for Neural Machine Translation","date":"2016-01-19","arxiv_id":"1601.04811","repositories_listed":3,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/modeling-coverage-for-neural-machine#ran","syntology_url":"https://syntology.ai/paper/1601.04811","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1601.04811"}},"official":{"repos":["tuzhaopeng/NMT-Coverage"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/unifying-visual-semantic-embeddings-with","slug":"unifying-visual-semantic-embeddings-with","title":"Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models","date":"2014-11-10","arxiv_id":"1411.2539","repositories_listed":3,"syntology":null},{"url":"/paper/on-the-properties-of-neural-machine","slug":"on-the-properties-of-neural-machine","title":"On the Properties of Neural Machine Translation: Encoder-Decoder Approaches","date":"2014-09-03","arxiv_id":"1409.1259","repositories_listed":3,"syntology":null},{"url":"/paper/do-not-change-me-on-transferring-entities","slug":"do-not-change-me-on-transferring-entities","title":"Do Not Change Me: On Transferring Entities Without Modification in Neural Machine Translation -- a Multilingual Perspective","date":"2025-05-09","arxiv_id":"2505.06010","repositories_listed":2,"syntology":null},{"url":"/paper/multimed-st-large-scale-many-to-many","slug":"multimed-st-large-scale-many-to-many","title":"MultiMed-ST: Large-scale Many-to-many Multilingual Medical Speech Translation","date":"2025-04-04","arxiv_id":"2504.03546","repositories_listed":2,"syntology":null},{"url":"/paper/automatic-input-rewriting-improves","slug":"automatic-input-rewriting-improves","title":"Automatic Input Rewriting Improves Translation with Large Language Models","date":"2025-02-23","arxiv_id":"2502.16682","repositories_listed":2,"syntology":null},{"url":"/paper/survey-on-abstractive-text-summarization","slug":"survey-on-abstractive-text-summarization","title":"Survey on Abstractive Text Summarization: Dataset, Models, and Metrics","date":"2024-12-22","arxiv_id":"2412.17165","repositories_listed":2,"syntology":null},{"url":"/paper/pos-tagging-to-highlight-the-skeletal","slug":"pos-tagging-to-highlight-the-skeletal","title":"POS-tagging to highlight the skeletal structure of sentences","date":"2024-11-21","arxiv_id":"2411.14393","repositories_listed":2,"syntology":null},{"url":"/paper/efficient-machine-translation-with-a-bilstm","slug":"efficient-machine-translation-with-a-bilstm","title":"Efficient Machine Translation with a BiLSTM-Attention Approach","date":"2024-10-29","arxiv_id":"2410.22335","repositories_listed":2,"syntology":null},{"url":"/paper/towards-zero-shot-multimodal-machine","slug":"towards-zero-shot-multimodal-machine","title":"Towards Zero-Shot Multimodal Machine Translation","date":"2024-07-18","arxiv_id":"2407.13579","repositories_listed":2,"syntology":null},{"url":"/paper/lexically-grounded-subword-segmentation","slug":"lexically-grounded-subword-segmentation","title":"Lexically Grounded Subword Segmentation","date":"2024-06-19","arxiv_id":"2406.13560","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/lexically-grounded-subword-segmentation#ran","syntology_url":"https://syntology.ai/paper/2406.13560","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.13560"}},"official":{"repos":["ufal/legros","ufal/legros-paper"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/low-resource-machine-translation-through-the","slug":"low-resource-machine-translation-through-the","title":"Low-Resource Machine Translation through the Lens of Personalized Federated Learning","date":"2024-06-18","arxiv_id":"2406.12564","repositories_listed":2,"syntology":null},{"url":"/paper/error-span-annotation-a-balanced-approach-for","slug":"error-span-annotation-a-balanced-approach-for","title":"Error Span Annotation: A Balanced Approach for Human Evaluation of Machine Translation","date":"2024-06-17","arxiv_id":"2406.11580","repositories_listed":2,"syntology":null},{"url":"/paper/perhaps-beyond-human-translation-harnessing","slug":"perhaps-beyond-human-translation-harnessing","title":"(Perhaps) Beyond Human Translation: Harnessing Multi-Agent Collaboration for Translating Ultra-Long Literary Texts","date":"2024-05-20","arxiv_id":"2405.11804","repositories_listed":2,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/perhaps-beyond-human-translation-harnessing#ran","syntology_url":"https://syntology.ai/paper/2405.11804","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.11804"}},"official":{"repos":["minghao-wu/transagents"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/benchmarking-large-language-models-on-cflue-a","slug":"benchmarking-large-language-models-on-cflue-a","title":"Benchmarking Large Language Models on CFLUE -- A Chinese Financial Language Understanding Evaluation Dataset","date":"2024-05-17","arxiv_id":"2405.10542","repositories_listed":2,"syntology":null},{"url":"/paper/mind-your-language-a-multilingual-dataset-for","slug":"mind-your-language-a-multilingual-dataset-for","title":"MIND Your Language: A Multilingual Dataset for Cross-lingual News Recommendation","date":"2024-03-26","arxiv_id":"2403.17876","repositories_listed":2,"syntology":null},{"url":"/paper/triples-to-isixhosa-t2x-addressing-the","slug":"triples-to-isixhosa-t2x-addressing-the","title":"Triples-to-isiXhosa (T2X): Addressing the Challenges of Low-Resource Agglutinative Data-to-Text Generation","date":"2024-03-12","arxiv_id":"2403.07567","repositories_listed":2,"syntology":null},{"url":"/paper/climategpt-towards-ai-synthesizing","slug":"climategpt-towards-ai-synthesizing","title":"ClimateGPT: Towards AI Synthesizing Interdisciplinary Research on Climate Change","date":"2024-01-17","arxiv_id":"2401.09646","repositories_listed":2,"syntology":{"n":20,"n_ran":19,"n_constructed":0,"n_ran_checked":19,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":19,"n_pointer_only":20,"phrase":"19 ran (of which 0 constructed an object rather than computing a result; 19 with no instrument failure: 0 honoured, 0 violated, 19 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/climategpt-towards-ai-synthesizing#ran","syntology_url":"https://syntology.ai/paper/2401.09646","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.09646"}},"official":{"repos":["eci-io/climategpt-evaluation"],"state":"official (archive's flag): 19 ran","n_ran":19,"n_constructed":0,"n_ran_no_instrument_failure":19,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/navigating-the-metrics-maze-reconciling-score","slug":"navigating-the-metrics-maze-reconciling-score","title":"Navigating the Metrics Maze: Reconciling Score Magnitudes and Accuracies","date":"2024-01-12","arxiv_id":"2401.06760","repositories_listed":2,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/navigating-the-metrics-maze-reconciling-score#ran","syntology_url":"https://syntology.ai/paper/2401.06760","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.06760"}},"official":{"repos":["kocmitom/mt-thresholds"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/fine-tuning-large-language-models-for-1","slug":"fine-tuning-large-language-models-for-1","title":"Fine-tuning Large Language Models for Adaptive Machine Translation","date":"2023-12-20","arxiv_id":"2312.12740","repositories_listed":2,"syntology":null},{"url":"/paper/opuscleaner-and-opustrainer-open-source","slug":"opuscleaner-and-opustrainer-open-source","title":"OpusCleaner and OpusTrainer, open source toolkits for training Machine Translation and Large language models","date":"2023-11-24","arxiv_id":"2311.14838","repositories_listed":2,"syntology":null},{"url":"/paper/lauragpt-listen-attend-understand-and","slug":"lauragpt-listen-attend-understand-and","title":"LauraGPT: Listen, Attend, Understand, and Regenerate Audio with GPT","date":"2023-10-07","arxiv_id":"2310.04673","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/lauragpt-listen-attend-understand-and#ran","syntology_url":"https://syntology.ai/paper/2310.04673","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.04673"}},"official":null}},{"url":"/paper/efficient-post-training-quantization-with-fp8","slug":"efficient-post-training-quantization-with-fp8","title":"Efficient Post-training Quantization with FP8 Formats","date":"2023-09-26","arxiv_id":"2309.14592","repositories_listed":2,"syntology":null},{"url":"/paper/signbank-multilingual-sign-language","slug":"signbank-multilingual-sign-language","title":"SignBank+: Preparing a Multilingual Sign Language Dataset for Machine Translation Using Large Language Models","date":"2023-09-20","arxiv_id":"2309.11566","repositories_listed":2,"syntology":null},{"url":"/paper/chatgpt-mt-competitive-for-high-but-not-low","slug":"chatgpt-mt-competitive-for-high-but-not-low","title":"ChatGPT MT: Competitive for High- (but not Low-) Resource Languages","date":"2023-09-14","arxiv_id":"2309.07423","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/chatgpt-mt-competitive-for-high-but-not-low#ran","syntology_url":"https://syntology.ai/paper/2309.07423","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.07423"}},"official":{"repos":["cmu-llab/gpt_mt_benchmark"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/sib-200-a-simple-inclusive-and-big-evaluation","slug":"sib-200-a-simple-inclusive-and-big-evaluation","title":"SIB-200: A Simple, Inclusive, and Big Evaluation Dataset for Topic Classification in 200+ Languages and Dialects","date":"2023-09-14","arxiv_id":"2309.07445","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/sib-200-a-simple-inclusive-and-big-evaluation#ran","syntology_url":"https://syntology.ai/paper/2309.07445","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.07445"}},"official":{"repos":["dadelani/sib-200"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}}],"record_sha256":"c6ebce1a57e713beef9736497fad47b51f887eeacea6eb08c3099f13746f167a","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}