{"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/translation/papers/28","list_of":"/task/translation","task":"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":28,"pages_in_order":124,"rows_per_page":100,"rows":[2701,2800],"of":12395,"counts":{"archive_papers_tagged":12395,"with_a_code_link":3574,"where_syntology_ran_a_sample":682,"not_listed_spam_title":0,"listed":12395,"listed_where_code_ran":682,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":566,"every_run_a_failure_of_syntologys_instrument":116,"listed_with_a_run_with_no_instrument_failure":566,"listed_every_run_a_failure_of_syntologys_instrument":116,"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/translation","prev":"/task/translation/papers/27","next":"/task/translation/papers/29","papers":[{"url":"/paper/domain-adaptation-for-image-dehazing","slug":"domain-adaptation-for-image-dehazing","title":"Domain Adaptation for Image Dehazing","date":"2020-05-10","arxiv_id":"2005.04668","repositories_listed":1,"syntology":null},{"url":"/paper/diversifying-dialogue-generation-with-non","slug":"diversifying-dialogue-generation-with-non","title":"Diversifying Dialogue Generation with Non-Conversational Text","date":"2020-05-09","arxiv_id":"2005.04346","repositories_listed":1,"syntology":null},{"url":"/paper/does-multi-encoder-help-a-case-study-on","slug":"does-multi-encoder-help-a-case-study-on","title":"Does Multi-Encoder Help? A Case Study on Context-Aware Neural Machine Translation","date":"2020-05-07","arxiv_id":"2005.03393","repositories_listed":1,"syntology":null},{"url":"/paper/jass-japanese-specific-sequence-to-sequence","slug":"jass-japanese-specific-sequence-to-sequence","title":"JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation","date":"2020-05-07","arxiv_id":"2005.03361","repositories_listed":1,"syntology":null},{"url":"/paper/on-exposure-bias-hallucination-and-domain","slug":"on-exposure-bias-hallucination-and-domain","title":"On Exposure Bias, Hallucination and Domain Shift in Neural Machine Translation","date":"2020-05-07","arxiv_id":"2005.03642","repositories_listed":1,"syntology":null},{"url":"/paper/deephist-differentiable-joint-and-color","slug":"deephist-differentiable-joint-and-color","title":"DeepHist: Differentiable Joint and Color Histogram Layers for Image-to-Image Translation","date":"2020-05-06","arxiv_id":"2005.03995","repositories_listed":1,"syntology":null},{"url":"/paper/it-s-easier-to-translate-out-of-english-than","slug":"it-s-easier-to-translate-out-of-english-than","title":"It's Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information","date":"2020-05-05","arxiv_id":"2005.02354","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":2,"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) · 2 unverified","sample_list":"/paper/it-s-easier-to-translate-out-of-english-than#ran","syntology_url":"https://syntology.ai/paper/2005.02354","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.02354"}},"official":{"repos":["e-bug/nmt-difficulty"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/stereogan-bridging-synthetic-to-real-domain","slug":"stereogan-bridging-synthetic-to-real-domain","title":"StereoGAN: Bridging Synthetic-to-Real Domain Gap by Joint Optimization of Domain Translation and Stereo Matching","date":"2020-05-05","arxiv_id":"2005.01927","repositories_listed":1,"syntology":null},{"url":"/paper/dynamic-programming-encoding-for-subword","slug":"dynamic-programming-encoding-for-subword","title":"Dynamic Programming Encoding for Subword Segmentation in Neural Machine Translation","date":"2020-05-03","arxiv_id":"2005.06606","repositories_listed":1,"syntology":null},{"url":"/paper/how-does-selective-mechanism-improve-self","slug":"how-does-selective-mechanism-improve-self","title":"How Does Selective Mechanism Improve Self-Attention Networks?","date":"2020-05-03","arxiv_id":"2005.00979","repositories_listed":1,"syntology":null},{"url":"/paper/on-the-inference-calibration-of-neural","slug":"on-the-inference-calibration-of-neural","title":"On the Inference Calibration of Neural Machine Translation","date":"2020-05-03","arxiv_id":"2005.00963","repositories_listed":1,"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/on-the-inference-calibration-of-neural#ran","syntology_url":"https://syntology.ai/paper/2005.00963","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.00963"}},"official":{"repos":["shuo-git/InfECE"],"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/on-the-limitations-of-cross-lingual-encoders","slug":"on-the-limitations-of-cross-lingual-encoders","title":"On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation","date":"2020-05-03","arxiv_id":"2005.01196","repositories_listed":1,"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":1,"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/on-the-limitations-of-cross-lingual-encoders#ran","syntology_url":"https://syntology.ai/paper/2005.01196","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.01196"}},"official":{"repos":["AIPHES/ACL20-Reference-Free-MT-Evaluation"],"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","unlocated"]}}},{"url":"/paper/engine-energy-based-inference-networks-for","slug":"engine-energy-based-inference-networks-for","title":"ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation","date":"2020-05-02","arxiv_id":"2005.00850","repositories_listed":1,"syntology":null},{"url":"/paper/hard-coded-gaussian-attention-for-neural","slug":"hard-coded-gaussian-attention-for-neural","title":"Hard-Coded Gaussian Attention for Neural Machine Translation","date":"2020-05-02","arxiv_id":"2005.00742","repositories_listed":1,"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/hard-coded-gaussian-attention-for-neural#ran","syntology_url":"https://syntology.ai/paper/2005.00742","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.00742"}},"official":{"repos":["fallcat/stupidNMT"],"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/synthesizer-rethinking-self-attention-in","slug":"synthesizer-rethinking-self-attention-in","title":"Synthesizer: Rethinking Self-Attention in Transformer Models","date":"2020-05-02","arxiv_id":"2005.00743","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"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 1 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; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/synthesizer-rethinking-self-attention-in#ran","syntology_url":"https://syntology.ai/paper/2005.00743","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.00743"}},"official":null}},{"url":"/paper/an-evaluation-benchmark-for-testing-the-word","slug":"an-evaluation-benchmark-for-testing-the-word","title":"An Evaluation Benchmark for Testing the Word Sense Disambiguation Capabilities of Machine Translation Systems","date":"2020-05-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/benchmarking-multidomain-english-indonesian","slug":"benchmarking-multidomain-english-indonesian","title":"Benchmarking Multidomain English-Indonesian Machine Translation","date":"2020-05-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/comparing-statistical-and-neural-models-for","slug":"comparing-statistical-and-neural-models-for","title":"Comparing Statistical and Neural Models for Learning Sound Correspondences","date":"2020-05-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/compositional-language-continual-learning","slug":"compositional-language-continual-learning","title":"Compositional Language Continual Learning","date":"2020-05-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/masked-based-unsupervised-content-transfer","slug":"masked-based-unsupervised-content-transfer","title":"Masked Based Unsupervised Content Transfer","date":"2020-05-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/methodological-aspects-of-developing-and","slug":"methodological-aspects-of-developing-and","title":"Methodological Aspects of Developing and Managing an Etymological Lexical Resource: Introducing EtymDB-2.0","date":"2020-05-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/multiseg-parallel-data-and-subword","slug":"multiseg-parallel-data-and-subword","title":"MultiSeg: Parallel Data and Subword Information for Learning Bilingual Embeddings in Low Resource Scenarios","date":"2020-05-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/neural-machine-translation-with-universal","slug":"neural-machine-translation-with-universal","title":"Neural Machine Translation with Universal Visual Representation","date":"2020-05-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/sedar-a-large-scale-french-english-financial","slug":"sedar-a-large-scale-french-english-financial","title":"SEDAR: a Large Scale French-English Financial Domain Parallel Corpus","date":"2020-05-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/towards-kurdish-text-to-sign-translation","slug":"towards-kurdish-text-to-sign-translation","title":"Towards Kurdish Text to Sign Translation","date":"2020-05-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/xcopa-a-multilingual-dataset-for-causal","slug":"xcopa-a-multilingual-dataset-for-causal","title":"XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning","date":"2020-05-01","arxiv_id":"2005.00333","repositories_listed":1,"syntology":null},{"url":"/paper/accurate-word-alignment-induction-from-neural","slug":"accurate-word-alignment-induction-from-neural","title":"Accurate Word Alignment Induction from Neural Machine Translation","date":"2020-04-30","arxiv_id":"2004.14837","repositories_listed":1,"syntology":null},{"url":"/paper/automatic-machine-translation-evaluation-in","slug":"automatic-machine-translation-evaluation-in","title":"Automatic Machine Translation Evaluation in Many Languages via Zero-Shot Paraphrasing","date":"2020-04-30","arxiv_id":"2004.14564","repositories_listed":1,"syntology":null},{"url":"/paper/bridging-linguistic-typology-and-multilingual","slug":"bridging-linguistic-typology-and-multilingual","title":"Bridging Linguistic Typology and Multilingual Machine Translation with Multi-View Language Representations","date":"2020-04-30","arxiv_id":"2004.14923","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/bridging-linguistic-typology-and-multilingual#ran","syntology_url":"https://syntology.ai/paper/2004.14923","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.14923"}},"official":{"repos":["aoncevay/multiview-langrep"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/imitation-attacks-and-defenses-for-black-box","slug":"imitation-attacks-and-defenses-for-black-box","title":"Imitation Attacks and Defenses for Black-box Machine Translation Systems","date":"2020-04-30","arxiv_id":"2004.15015","repositories_listed":1,"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/imitation-attacks-and-defenses-for-black-box#ran","syntology_url":"https://syntology.ai/paper/2004.15015","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.15015"}},"official":{"repos":["Eric-Wallace/adversarial-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/language-model-prior-for-low-resource-neural","slug":"language-model-prior-for-low-resource-neural","title":"Language Model Prior for Low-Resource Neural Machine Translation","date":"2020-04-30","arxiv_id":"2004.14928","repositories_listed":1,"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/language-model-prior-for-low-resource-neural#ran","syntology_url":"https://syntology.ai/paper/2004.14928","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.14928"}},"official":{"repos":["cbaziotis/lm-prior-for-nmt"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/mind-your-inflections-improving-nlp-for-non","slug":"mind-your-inflections-improving-nlp-for-non","title":"Mind Your Inflections! Improving NLP for Non-Standard Englishes with Base-Inflection Encoding","date":"2020-04-30","arxiv_id":"2004.14870","repositories_listed":1,"syntology":null},{"url":"/paper/nubia-neural-based-interchangeability","slug":"nubia-neural-based-interchangeability","title":"NUBIA: NeUral Based Interchangeability Assessor for Text Generation","date":"2020-04-30","arxiv_id":"2004.14667","repositories_listed":1,"syntology":null},{"url":"/paper/progressive-transformers-for-end-to-end-sign","slug":"progressive-transformers-for-end-to-end-sign","title":"Progressive Transformers for End-to-End Sign Language Production","date":"2020-04-30","arxiv_id":"2004.14874","repositories_listed":1,"syntology":null},{"url":"/paper/simulated-multiple-reference-training","slug":"simulated-multiple-reference-training","title":"Simulated Multiple Reference Training Improves Low-Resource Machine Translation","date":"2020-04-30","arxiv_id":"2004.14524","repositories_listed":1,"syntology":{"n":5,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":5,"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) · 3 unverified","sample_list":"/paper/simulated-multiple-reference-training#ran","syntology_url":"https://syntology.ai/paper/2004.14524","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.14524"}},"official":null}},{"url":"/paper/use-of-machine-translation-to-obtain-labeled","slug":"use-of-machine-translation-to-obtain-labeled","title":"Data and Representation for Turkish Natural Language Inference","date":"2020-04-30","arxiv_id":"2004.14963","repositories_listed":1,"syntology":null},{"url":"/paper/adversarial-subword-regularization-for-robust","slug":"adversarial-subword-regularization-for-robust","title":"Adversarial Subword Regularization for Robust Neural Machine Translation","date":"2020-04-29","arxiv_id":"2004.14109","repositories_listed":1,"syntology":null},{"url":"/paper/learning-non-monotonic-automatic-post-editing","slug":"learning-non-monotonic-automatic-post-editing","title":"Learning Non-Monotonic Automatic Post-Editing of Translations from Human Orderings","date":"2020-04-29","arxiv_id":"2004.14120","repositories_listed":1,"syntology":null},{"url":"/paper/multiscale-collaborative-deep-models-for","slug":"multiscale-collaborative-deep-models-for","title":"Multiscale Collaborative Deep Models for Neural Machine Translation","date":"2020-04-29","arxiv_id":"2004.14021","repositories_listed":1,"syntology":null},{"url":"/paper/conversational-word-embedding-for-retrieval","slug":"conversational-word-embedding-for-retrieval","title":"Conversational Word Embedding for Retrieval-Based Dialog System","date":"2020-04-28","arxiv_id":"2004.13249","repositories_listed":1,"syntology":null},{"url":"/paper/scheduled-drophead-a-regularization-method","slug":"scheduled-drophead-a-regularization-method","title":"Scheduled DropHead: A Regularization Method for Transformer Models","date":"2020-04-28","arxiv_id":"2004.13342","repositories_listed":1,"syntology":null},{"url":"/paper/towards-prediction-explainability-through","slug":"towards-prediction-explainability-through","title":"The Explanation Game: Towards Prediction Explainability through Sparse Communication","date":"2020-04-28","arxiv_id":"2004.13876","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/towards-prediction-explainability-through#ran","syntology_url":"https://syntology.ai/paper/2004.13876","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.13876"}},"official":{"repos":["deep-spin/spec"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/difficulty-translation-in-histopathology","slug":"difficulty-translation-in-histopathology","title":"Difficulty Translation in Histopathology Images","date":"2020-04-27","arxiv_id":"2004.12535","repositories_listed":1,"syntology":null},{"url":"/paper/lexically-constrained-neural-machine","slug":"lexically-constrained-neural-machine","title":"Lexically Constrained Neural Machine Translation with Levenshtein Transformer","date":"2020-04-27","arxiv_id":"2004.12681","repositories_listed":1,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":4,"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) · 2 unverified","sample_list":"/paper/lexically-constrained-neural-machine#ran","syntology_url":"https://syntology.ai/paper/2004.12681","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.12681"}},"official":{"repos":["raymondhs/constrained-levt"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/neural-machine-translation-with-monte-carlo","slug":"neural-machine-translation-with-monte-carlo","title":"Neural Machine Translation with Monte-Carlo Tree Search","date":"2020-04-27","arxiv_id":"2004.12527","repositories_listed":1,"syntology":null},{"url":"/paper/all-word-embeddings-from-one-embedding","slug":"all-word-embeddings-from-one-embedding","title":"All Word Embeddings from One Embedding","date":"2020-04-25","arxiv_id":"2004.12073","repositories_listed":1,"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/all-word-embeddings-from-one-embedding#ran","syntology_url":"https://syntology.ai/paper/2004.12073","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.12073"}},"official":{"repos":["takase/alone_seq2seq"],"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/g-daug-generative-data-augmentation-for","slug":"g-daug-generative-data-augmentation-for","title":"Generative Data Augmentation for Commonsense Reasoning","date":"2020-04-24","arxiv_id":"2004.11546","repositories_listed":1,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":4,"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) · 2 unverified","sample_list":"/paper/g-daug-generative-data-augmentation-for#ran","syntology_url":"https://syntology.ai/paper/2004.11546","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.11546"}},"official":{"repos":["yangyiben/G-DAUG-c-Generative-Data-Augmentation-for-Commonsense-Reasoning"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/practical-comparable-data-collection-for-low","slug":"practical-comparable-data-collection-for-low","title":"Practical Comparable Data Collection for Low-Resource Languages via Images","date":"2020-04-24","arxiv_id":"2004.11954","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"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) · 1 unverified","sample_list":"/paper/practical-comparable-data-collection-for-low#ran","syntology_url":"https://syntology.ai/paper/2004.11954","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.11954"}},"official":{"repos":["madaan/PML4DC-Comparable-Data-Collection"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/correct-me-if-you-can-learning-from-error","slug":"correct-me-if-you-can-learning-from-error","title":"Correct Me If You Can: Learning from Error Corrections and Markings","date":"2020-04-23","arxiv_id":"2004.11222","repositories_listed":1,"syntology":null},{"url":"/paper/semi-supervised-models-via-data","slug":"semi-supervised-models-via-data","title":"Semi-Supervised Models via Data Augmentationfor Classifying Interactive Affective Responses","date":"2020-04-23","arxiv_id":"2004.10972","repositories_listed":1,"syntology":null},{"url":"/paper/residual-energy-based-models-for-text-1","slug":"residual-energy-based-models-for-text-1","title":"Residual Energy-Based Models for Text Generation","date":"2020-04-22","arxiv_id":"2004.11714","repositories_listed":1,"syntology":null},{"url":"/paper/attention-module-is-not-only-a-weight","slug":"attention-module-is-not-only-a-weight","title":"Attention is Not Only a Weight: Analyzing Transformers with Vector Norms","date":"2020-04-21","arxiv_id":"2004.10102","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":4,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/attention-module-is-not-only-a-weight#ran","syntology_url":"https://syntology.ai/paper/2004.10102","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.10102"}},"official":{"repos":["gorokoba560/norm-analysis-of-transformer"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/contextual-neural-machine-translation","slug":"contextual-neural-machine-translation","title":"Contextual Neural Machine Translation Improves Translation of Cataphoric Pronouns","date":"2020-04-21","arxiv_id":"2004.09894","repositories_listed":1,"syntology":null},{"url":"/paper/espnet-st-all-in-one-speech-translation","slug":"espnet-st-all-in-one-speech-translation","title":"ESPnet-ST: All-in-One Speech Translation Toolkit","date":"2020-04-21","arxiv_id":"2004.10234","repositories_listed":1,"syntology":null},{"url":"/paper/how-to-track-your-dragon-a-multi-attentional","slug":"how-to-track-your-dragon-a-multi-attentional","title":"How to track your dragon: A Multi-Attentional Framework for real-time RGB-D 6-DOF Object Pose Tracking","date":"2020-04-21","arxiv_id":"2004.10335","repositories_listed":1,"syntology":null},{"url":"/paper/desmoking-laparoscopy-surgery-images-using-an","slug":"desmoking-laparoscopy-surgery-images-using-an","title":"Desmoking laparoscopy surgery images using an image-to-image translation guided by an embedded dark channel","date":"2020-04-19","arxiv_id":"2004.08947","repositories_listed":1,"syntology":null},{"url":"/paper/neural-machine-translation-for-low-resourced","slug":"neural-machine-translation-for-low-resourced","title":"Neural Machine Translation for Low-Resourced Indian Languages","date":"2020-04-19","arxiv_id":"2004.13819","repositories_listed":1,"syntology":null},{"url":"/paper/code-aligned-autoencoders-for-unsupervised","slug":"code-aligned-autoencoders-for-unsupervised","title":"Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images","date":"2020-04-15","arxiv_id":"2004.07011","repositories_listed":1,"syntology":null},{"url":"/paper/cross-lingual-semantic-role-labeling-with","slug":"cross-lingual-semantic-role-labeling-with","title":"Cross-Lingual Semantic Role Labeling with High-Quality Translated Training Corpus","date":"2020-04-14","arxiv_id":"2004.06295","repositories_listed":1,"syntology":{"n":2,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"0 ran · 2 unverified","sample_list":"/paper/cross-lingual-semantic-role-labeling-with#ran","syntology_url":"https://syntology.ai/paper/2004.06295","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.06295"}},"official":{"repos":["scofield7419/XSRL-ACL"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":[]}}},{"url":"/paper/transformer-based-grapheme-to-phoneme-1","slug":"transformer-based-grapheme-to-phoneme-1","title":"Transformer based Grapheme-to-Phoneme Conversion","date":"2020-04-14","arxiv_id":"2004.06338","repositories_listed":1,"syntology":null},{"url":"/paper/neural-machine-translation-challenges","slug":"neural-machine-translation-challenges","title":"Neural Machine Translation: Challenges, Progress and Future","date":"2020-04-13","arxiv_id":"2004.05809","repositories_listed":1,"syntology":null},{"url":"/paper/lareqa-language-agnostic-answer-retrieval","slug":"lareqa-language-agnostic-answer-retrieval","title":"LAReQA: Language-agnostic answer retrieval from a multilingual pool","date":"2020-04-11","arxiv_id":"2004.05484","repositories_listed":1,"syntology":null},{"url":"/paper/object-centered-fourier-motion-estimation-and","slug":"object-centered-fourier-motion-estimation-and","title":"Object-centered Fourier Motion Estimation and Segment-Transformation Prediction","date":"2020-04-11","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/asl-recognition-with-metric-learning-based-1","slug":"asl-recognition-with-metric-learning-based-1","title":"ASL Recognition with Metric-Learning based Lightweight Network","date":"2020-04-10","arxiv_id":"2004.05054","repositories_listed":1,"syntology":null},{"url":"/paper/weakly-supervised-multiple-instance-learning","slug":"weakly-supervised-multiple-instance-learning","title":"Weakly supervised multiple instance learning histopathological tumor segmentation","date":"2020-04-10","arxiv_id":"2004.05024","repositories_listed":1,"syntology":null},{"url":"/paper/on-optimal-transformer-depth-for-low-resource","slug":"on-optimal-transformer-depth-for-low-resource","title":"On Optimal Transformer Depth for Low-Resource Language Translation","date":"2020-04-09","arxiv_id":"2004.04418","repositories_listed":1,"syntology":null},{"url":"/paper/translation-artifacts-in-cross-lingual","slug":"translation-artifacts-in-cross-lingual","title":"Translation Artifacts in Cross-lingual Transfer Learning","date":"2020-04-09","arxiv_id":"2004.04721","repositories_listed":1,"syntology":null},{"url":"/paper/tuigan-learning-versatile-image-to-image","slug":"tuigan-learning-versatile-image-to-image","title":"TuiGAN: Learning Versatile Image-to-Image Translation with Two Unpaired Images","date":"2020-04-09","arxiv_id":"2004.04634","repositories_listed":1,"syntology":null},{"url":"/paper/transfer-learning-and-subword-sampling-for","slug":"transfer-learning-and-subword-sampling-for","title":"Transfer learning and subword sampling for asymmetric-resource one-to-many neural translation","date":"2020-04-08","arxiv_id":"2004.04002","repositories_listed":1,"syntology":null},{"url":"/paper/dynamic-data-selection-and-weighting-for","slug":"dynamic-data-selection-and-weighting-for","title":"Dynamic Data Selection and Weighting for Iterative Back-Translation","date":"2020-04-07","arxiv_id":"2004.03672","repositories_listed":1,"syntology":null},{"url":"/paper/graph-to-tree-neural-networks-for-learning","slug":"graph-to-tree-neural-networks-for-learning","title":"Graph-to-Tree Neural Networks for Learning Structured Input-Output Translation with Applications to Semantic Parsing and Math Word Problem","date":"2020-04-07","arxiv_id":"2004.13781","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 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) · 0 unverified","sample_list":"/paper/graph-to-tree-neural-networks-for-learning#ran","syntology_url":"https://syntology.ai/paper/2004.13781","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.13781"}},"official":{"repos":["IBM/Graph2Tree"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/towards-multimodal-simultaneous-neural","slug":"towards-multimodal-simultaneous-neural","title":"Towards Multimodal Simultaneous Neural Machine Translation","date":"2020-04-07","arxiv_id":"2004.03180","repositories_listed":1,"syntology":null},{"url":"/paper/bootstrapping-a-crosslingual-semantic-parser","slug":"bootstrapping-a-crosslingual-semantic-parser","title":"Bootstrapping a Crosslingual Semantic Parser","date":"2020-04-06","arxiv_id":"2004.02585","repositories_listed":1,"syntology":null},{"url":"/paper/neural-machine-translation-with-imbalanced","slug":"neural-machine-translation-with-imbalanced","title":"Finding the Optimal Vocabulary Size for Neural Machine Translation","date":"2020-04-05","arxiv_id":"2004.02334","repositories_listed":1,"syntology":null},{"url":"/paper/neuron-linear-transformation-modeling-the","slug":"neuron-linear-transformation-modeling-the","title":"Neuron Linear Transformation: Modeling the Domain Shift for Crowd Counting","date":"2020-04-05","arxiv_id":"2004.02133","repositories_listed":1,"syntology":null},{"url":"/paper/reference-language-based-unsupervised-neural","slug":"reference-language-based-unsupervised-neural","title":"Reference Language based Unsupervised Neural Machine Translation","date":"2020-04-05","arxiv_id":"2004.02127","repositories_listed":1,"syntology":null},{"url":"/paper/structural-analogy-from-a-single-image-pair","slug":"structural-analogy-from-a-single-image-pair","title":"Structural-analogy from a Single Image Pair","date":"2020-04-05","arxiv_id":"2004.02222","repositories_listed":1,"syntology":null},{"url":"/paper/unsupervised-domain-clusters-in-pretrained","slug":"unsupervised-domain-clusters-in-pretrained","title":"Unsupervised Domain Clusters in Pretrained Language Models","date":"2020-04-05","arxiv_id":"2004.02105","repositories_listed":1,"syntology":null},{"url":"/paper/a-set-of-recommendations-for-assessing-human","slug":"a-set-of-recommendations-for-assessing-human","title":"A Set of Recommendations for Assessing Human-Machine Parity in Language Translation","date":"2020-04-03","arxiv_id":"2004.01694","repositories_listed":1,"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":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) · 0 unverified","sample_list":"/paper/a-set-of-recommendations-for-assessing-human#ran","syntology_url":"https://syntology.ai/paper/2004.01694","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.01694"}},"official":{"repos":["ZurichNLP/mt-parity-assessment-data"],"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/aligned-cross-entropy-for-non-autoregressive","slug":"aligned-cross-entropy-for-non-autoregressive","title":"Aligned Cross Entropy for Non-Autoregressive Machine Translation","date":"2020-04-03","arxiv_id":"2004.01655","repositories_listed":1,"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":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) · 0 unverified","sample_list":"/paper/aligned-cross-entropy-for-non-autoregressive#ran","syntology_url":"https://syntology.ai/paper/2004.01655","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.01655"}},"official":null}},{"url":"/paper/volumetric-landmark-detection-with-a-multi-1","slug":"volumetric-landmark-detection-with-a-multi-1","title":"Volumetric landmark detection with a multi-scale translation equivariant neural network","date":"2020-04-03","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/sign-language-translation-with-transformers","slug":"sign-language-translation-with-transformers","title":"Better Sign Language Translation with STMC-Transformer","date":"2020-04-01","arxiv_id":"2004.00588","repositories_listed":1,"syntology":{"n":5,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":1,"n_no_contract":1,"n_pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 1 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/sign-language-translation-with-transformers#ran","syntology_url":"https://syntology.ai/paper/2004.00588","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.00588"}},"official":{"repos":["kayoyin/transformer-slt"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/low-resource-neural-machine-translation-a","slug":"low-resource-neural-machine-translation-a","title":"Low Resource Neural Machine Translation: A Benchmark for Five African Languages","date":"2020-03-31","arxiv_id":"2003.14402","repositories_listed":1,"syntology":null},{"url":"/paper/towards-lifelong-self-supervision-for","slug":"towards-lifelong-self-supervision-for","title":"Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation","date":"2020-03-31","arxiv_id":"2004.00161","repositories_listed":1,"syntology":null},{"url":"/paper/semi-supervised-learning-for-few-shot-image","slug":"semi-supervised-learning-for-few-shot-image","title":"Semi-supervised Learning for Few-shot Image-to-Image Translation","date":"2020-03-30","arxiv_id":"2003.13853","repositories_listed":1,"syntology":null},{"url":"/paper/augmenting-colonoscopy-using-extended-and","slug":"augmenting-colonoscopy-using-extended-and","title":"Augmenting Colonoscopy using Extended and Directional CycleGAN for Lossy Image Translation","date":"2020-03-27","arxiv_id":"2003.12473","repositories_listed":1,"syntology":null},{"url":"/paper/towards-supervised-and-unsupervised-neural","slug":"towards-supervised-and-unsupervised-neural","title":"Towards Supervised and Unsupervised Neural Machine Translation Baselines for Nigerian Pidgin","date":"2020-03-27","arxiv_id":"2003.12660","repositories_listed":1,"syntology":null},{"url":"/paper/ffr-v1-0-fon-french-neural-machine","slug":"ffr-v1-0-fon-french-neural-machine","title":"FFR V1.0: Fon-French Neural Machine Translation","date":"2020-03-26","arxiv_id":"2003.12111","repositories_listed":1,"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/ffr-v1-0-fon-french-neural-machine#ran","syntology_url":"https://syntology.ai/paper/2003.12111","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.12111"}},"official":{"repos":["bonaventuredossou/ffr-v1"],"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/log-likelihood-ratio-minimizing-flows-towards","slug":"log-likelihood-ratio-minimizing-flows-towards","title":"Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment","date":"2020-03-26","arxiv_id":"2003.12170","repositories_listed":1,"syntology":null},{"url":"/paper/g2l-net-global-to-local-network-for-real-time","slug":"g2l-net-global-to-local-network-for-real-time","title":"G2L-Net: Global to Local Network for Real-time 6D Pose Estimation with Embedding Vector Features","date":"2020-03-24","arxiv_id":"2003.11089","repositories_listed":1,"syntology":null},{"url":"/paper/deep-multi-attributed-graph-translation-with","slug":"deep-multi-attributed-graph-translation-with","title":"Deep Multi-attributed Graph Translation with Node-Edge Co-evolution","date":"2020-03-22","arxiv_id":"2003.09945","repositories_listed":1,"syntology":null},{"url":"/paper/language-technology-programme-for-icelandic","slug":"language-technology-programme-for-icelandic","title":"Language Technology Programme for Icelandic 2019-2023","date":"2020-03-20","arxiv_id":"2003.09244","repositories_listed":1,"syntology":null},{"url":"/paper/high-resolution-daytime-translation-without","slug":"high-resolution-daytime-translation-without","title":"High-Resolution Daytime Translation Without Domain Labels","date":"2020-03-19","arxiv_id":"2003.08791","repositories_listed":1,"syntology":null},{"url":"/paper/unsupervised-multi-modal-image-registration","slug":"unsupervised-multi-modal-image-registration","title":"Unsupervised Multi-Modal Image Registration via Geometry Preserving Image-to-Image Translation","date":"2020-03-18","arxiv_id":"2003.08073","repositories_listed":1,"syntology":null},{"url":"/paper/xpersona-evaluating-multilingual-personalized","slug":"xpersona-evaluating-multilingual-personalized","title":"XPersona: Evaluating Multilingual Personalized Chatbot","date":"2020-03-17","arxiv_id":"2003.07568","repositories_listed":1,"syntology":null},{"url":"/paper/helfi-a-hebrew-greek-finnish-parallel-bible","slug":"helfi-a-hebrew-greek-finnish-parallel-bible","title":"HELFI: a Hebrew-Greek-Finnish Parallel Bible Corpus with Cross-Lingual Morpheme Alignment","date":"2020-03-16","arxiv_id":"2003.07456","repositories_listed":1,"syntology":null},{"url":"/paper/synthesizing-human-like-sketches-from-natural","slug":"synthesizing-human-like-sketches-from-natural","title":"Synthesizing human-like sketches from natural images using a conditional convolutional decoder","date":"2020-03-16","arxiv_id":"2003.07101","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/synthesizing-human-like-sketches-from-natural#ran","syntology_url":"https://syntology.ai/paper/2003.07101","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.07101"}},"official":{"repos":["kampelmuehler/synthesizing_human_like_sketches"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/gmm-unit-unsupervised-multi-domain-and-multi-1","slug":"gmm-unit-unsupervised-multi-domain-and-multi-1","title":"GMM-UNIT: Unsupervised Multi-Domain and Multi-Modal Image-to-Image Translation via Attribute Gaussian Mixture Modeling","date":"2020-03-15","arxiv_id":"2003.06788","repositories_listed":1,"syntology":null},{"url":"/paper/a-mobile-robot-hand-arm-teleoperation-system","slug":"a-mobile-robot-hand-arm-teleoperation-system","title":"A Mobile Robot Hand-Arm Teleoperation System by Vision and IMU","date":"2020-03-11","arxiv_id":"2003.05212","repositories_listed":1,"syntology":null},{"url":"/paper/deepurl-deep-pose-estimation-framework-for","slug":"deepurl-deep-pose-estimation-framework-for","title":"DeepURL: Deep Pose Estimation Framework for Underwater Relative Localization","date":"2020-03-11","arxiv_id":"2003.05523","repositories_listed":1,"syntology":null}],"record_sha256":"64cabc160ea6e27de8df247202e7c33af434eb8590fe1db8dc1b3ca37740e61c","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}