{"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/73","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":73,"pages_in_order":124,"rows_per_page":100,"rows":[7201,7300],"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/72","next":"/task/translation/papers/74","papers":[{"url":null,"slug":"elitr-european-live-translator","title":"ELITR: European Live Translator","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ellipsis-translation-for-a-medical-speech-to","title":"Ellipsis Translation for a Medical Speech to Speech Translation System","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"estimation-vs-metrics-is-qe-useful-for-mt","title":"Estimation vs Metrics: is QE Useful for MT Model Selection?","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"etranslations-submissions-to-the-wmt-2020","title":"eTranslation’s Submissions to the WMT 2020 News Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-the-usefulness-of-neural-machine","title":"Evaluating the usefulness of neural machine translation for the Polish translators in the European Commission","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluation-of-machine-translation-methods","title":"Evaluation of Machine Translation Methods applied to Medical Terminologies","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-coreference-features-in","title":"Exploring Coreference Features in Heterogeneous Data","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"extended-study-on-using-pretrained-language","title":"Extended Study on Using Pretrained Language Models and YiSi-1 for Machine Translation Evaluation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"facebook-ais-wmt20-news-translation-task","title":"Facebook AI’s WMT20 News Translation Task Submission","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"factorized-transformer-for-multi-domain","title":"Factorized Transformer for Multi-Domain Neural Machine Translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"findings-of-the-first-shared-task-on-lifelong","title":"Findings of the First Shared Task on Lifelong Learning Machine Translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"findings-of-the-wmt-2020-shared-task-on","title":"Findings of the WMT 2020 Shared Task on Machine Translation Robustness","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"findings-of-the-wmt-2020-shared-task-on-2","title":"Findings of the WMT 2020 Shared Task on Parallel Corpus Filtering and Alignment","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"findings-of-the-wmt-2020-shared-task-on-3","title":"Findings of the WMT 2020 Shared Task on Quality Estimation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fine-grained-error-analysis-on-english-to","title":"Fine-Grained Error Analysis on English-to-Japanese Machine Translation in the Medical Domain","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fjwu-participation-for-the-wmt20-biomedical","title":"FJWU participation for the WMT20 Biomedical Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"from-disjoint-sets-to-parallel-data-to-train","title":"From Disjoint Sets to Parallel Data to Train Seq2Seq Models for Sentiment Transfer","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"gtcom-neural-machine-translation-systems-for-1","title":"GTCOM Neural Machine Translation Systems for WMT20","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hindi-marathi-cross-lingual-model","title":"Hindi-Marathi Cross Lingual Model","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"how-do-lsps-compute-mt-discounts-presenting-a","title":"How do LSPs compute MT discounts? Presenting a company’s pipeline and its use","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"how-does-discourse-affect-spanish-chinese","title":"How does discourse affect Spanish-Chinese Translation? A case study based on a Spanish-Chinese parallel corpus","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"huaweis-submissions-to-the-wmt20-biomedical","title":"Huawei’s Submissions to the WMT20 Biomedical Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hw-tscs-participation-at-wmt-2020-automatic","title":"HW-TSC’s Participation at WMT 2020 Automatic Post Editing Shared Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hw-tscs-participation-in-the-wmt-2020-news","title":"HW-TSC’s Participation in the WMT 2020 News Translation Shared Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-emoji-based-masked-language-models-for","title":"Hybrid Emoji-Based Masked Language Models for Zero-Shot Abusive Language Detection","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"iies-neural-machine-translation-systems-for","title":"IIE’s Neural Machine Translation Systems for WMT20","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-parallel-data-identification-using","title":"Improving Parallel Data Identification using Iteratively Refined Sentence Alignments and Bilingual Mappings of Pre-trained Language Models","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-word-sense-disambiguation-with-1","title":"Improving Word Sense Disambiguation with Translations","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"incorporating-external-annotation-to-improve","title":"Incorporating External Annotation to improve Named Entity Translation in NMT","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"infosys-machine-translation-system-for-wmt20","title":"Infosys Machine Translation System for WMT20 Similar Language Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"insights-from-gathering-mt-productivity","title":"Insights from Gathering MT Productivity Metrics at Scale","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ist-unbabel-participation-in-the-wmt20","title":"IST-Unbabel Participation in the WMT20 Quality Estimation Shared Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"just-system-for-wmt20-chat-translation-task","title":"JUST System for WMT20 Chat Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-adaptive-segmentation-policy-for","title":"Learning Adaptive Segmentation Policy for Simultaneous Translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"limsi-wmt-2020","title":"LIMSI @ WMT 2020","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"linguistically-motivated-subwords-for-english","title":"Linguistically Motivated Subwords for English-Tamil Translation: University of Groningen’s Submission to WMT-2020","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"log-linear-reformulation-of-the-noisy-channel","title":"Log-Linear Reformulation of the Noisy Channel Model for Document-Level Neural Machine Translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"losing-heads-in-the-lottery-pruning","title":"Losing Heads in the Lottery: Pruning Transformer Attention in Neural Machine Translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"low-resource-translation-as-language-modeling","title":"Low-Resource Translation as Language Modeling","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-translation-for-english-inuktitut","title":"Machine Translation for English–Inuktitut with Segmentation, Data Acquisition and Pre-Training","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-translation-post-editing-levels","title":"Machine Translation Post-Editing Levels: Breaking Away from the Tradition and Delivering a Tailored Service","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-translation-quality-a-comparative","title":"Machine Translation Quality: A comparative evaluation of SMT, NMT and tailored-NMT outputs","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-translation-reference-less-evaluation","title":"Machine Translation Reference-less Evaluation using YiSi-2 with Bilingual Mappings of Massive Multilingual Language Model","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"modelling-source-and-target-language","title":"Modelling Source- and Target- Language Syntactic Information as Conditional Context in Interactive Neural Machine Translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"monolingual-adapters-for-zero-shot-neural","title":"Monolingual Adapters for Zero-Shot Neural Machine Translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mt-for-subtitling-user-evaluation-of-post","title":"MT for subtitling: User evaluation of post-editing productivity","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mt-syntactic-priming-effects-on-l2-english","title":"MT syntactic priming effects on L2 English speakers","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mtrill-project-machine-translation-impact-on","title":"MTrill project: Machine Translation impact on language learning","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mtuoc-easy-and-free-integration-of-nmt","title":"MTUOC: easy and free integration of NMT systems in professional translation environments","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-agent-mutual-learning-at-sentence-level","title":"Multi-Agent Mutual Learning at Sentence-Level and Token-Level for Neural Machine Translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multidimensional-assessment-of-the","title":"Multidimensional assessment of the eTranslation output for English–Slovene","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multilingual-neural-machine-translation-case","title":"Multilingual Neural Machine Translation: Case-study for Catalan, Spanish and Portuguese Romance Languages","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"natural-language-response-generation-from-sql","title":"Natural Language Response Generation from SQL with Generalization and Back-translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"naver-labs-europes-participation-in-the","title":"Naver Labs Europe’s Participation in the Robustness, Chat, and Biomedical Tasks at WMT 2020","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-machine-translation-between-similar","title":"Neural Machine Translation between similar South-Slavic languages","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-machine-translation-for-similar","title":"Neural Machine Translation for Similar Languages: The Case of Indo-Aryan Languages","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-translation-for-the-european-union","title":"Neural Translation for the European Union (NTEU) Project","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nice-neural-integrated-custom-engines","title":"NICE: Neural Integrated Custom Engines","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nict-kyoto-submission-for-the-wmt20-quality","title":"NICT Kyoto Submission for the WMT’20 Quality Estimation Task: Intermediate Training for Domain and Task Adaptation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nlprl-system-for-very-low-resource-supervised","title":"NLPRL System for Very Low Resource Supervised Machine Translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nmt-based-similar-language-translation-for","title":"NMT based Similar Language Translation for Hindi - Marathi","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nrc-systems-for-low-resource-german-upper","title":"NRC Systems for Low Resource German-Upper Sorbian Machine Translation 2020: Transfer Learning with Lexical Modifications","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nrc-systems-for-the-2020-inuktitut-english","title":"NRC Systems for the 2020 Inuktitut-English News Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nuig-panlingua-kmi-hindi-marathi-mt-systems","title":"NUIG-Panlingua-KMI Hindi-Marathi MT Systems for Similar Language Translation Task @ WMT 2020","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ocr-classification-machine-translation-occam","title":"OCR, Classification & Machine Translation (OCCAM)","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-differences-between-human-translations","title":"On the differences between human translations","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-evaluation-of-machine-translation-n","title":"On the Evaluation of Machine Translation n-best Lists","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-same-page-comparing-inter-annotator","title":"On the Same Page? Comparing Inter-Annotator Agreement in Sentence and Document Level Human Machine Translation Evaluation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"oppos-machine-translation-systems-for-wmt20","title":"OPPO’s Machine Translation Systems for WMT20","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/opus-mt-building-open-translation-services","slug":"opus-mt-building-open-translation-services","title":"OPUS-MT – Building open translation services for the World","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"parbleu-augmenting-metrics-with-automatic","title":"ParBLEU: Augmenting Metrics with Automatic Paraphrases for the WMT’20 Metrics Shared Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"patquest-papago-translation-quality","title":"PATQUEST: Papago Translation Quality Estimation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"posedion-post-editing-assessment-in-python","title":"PosEdiOn: Post-Editing Assessment in PythOn","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"postech-etris-submission-to-the-wmt2020-ape","title":"POSTECH-ETRI’s Submission to the WMT2020 APE Shared Task: Automatic Post-Editing with Cross-lingual Language Model","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"pre-tokenization-of-multi-word-expressions-in","title":"Pre-tokenization of Multi-word Expressions in Cross-lingual Word Embeddings","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"pretrained-language-models-and","title":"Pretrained Language Models and Backtranslation for English-Basque Biomedical Neural Machine Translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"priming-neural-machine-translation","title":"Priming Neural Machine Translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"progress-of-the-principle-project-promoting","title":"Progress of the PRINCIPLE Project: Promoting MT for Croatian, Icelandic, Irish and Norwegian","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"project-maia-multilingual-ai-agent-assistant","title":"Project MAIA: Multilingual AI Agent Assistant","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"promt-systems-for-wmt-2020-shared-news","title":"PROMT Systems for WMT 2020 Shared News Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"qrev-machine-translation-of-user-reviews-what","title":"QRev: Machine Translation of User Reviews: What Influences the Translation Quality?","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"quality-in-quality-out-learning-from-actual","title":"Quality In, Quality Out: Learning from Actual Mistakes","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"quantitative-analysis-of-post-editing-effort","title":"Quantitative Analysis of Post-Editing Effort Indicators for NMT","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"re-design-of-the-machine-translation-training","title":"Re-design of the Machine Translation Training Tool (MT3)","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"relations-between-comprehensibility-and","title":"Relations between comprehensibility and adequacy errors in machine translation output","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"results-of-the-wmt20-metrics-shared-task","title":"Results of the WMT20 Metrics Shared Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"revisiting-representation-degeneration","title":"Revisiting Representation Degeneration Problem in Language Modeling","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"rtm-ensemble-learning-results-at-quality","title":"RTM Ensemble Learning Results at Quality Estimation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"russian-english-bidirectional-machine","title":"Russian-English Bidirectional Machine Translation System","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"samsung-r-d-institute-poland-submission-to-1","title":"Samsung R&D Institute Poland submission to WMT20 News Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"simultaneous-translation","title":"Simultaneous Translation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sjtu-nicts-supervised-and-unsupervised-neural","title":"SJTU-NICT’s Supervised and Unsupervised Neural Machine Translation Systems for the WMT20 News Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-and-decorrelated-representations-for","title":"Sparse and Decorrelated Representations for Stable Zero-shot NMT","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"speed-optimized-compact-student-models-that","title":"Speed-optimized, Compact Student Models that Distill Knowledge from a Larger Teacher Model: the UEDIN-CUNI Submission to the WMT 2020 News Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"statistical-power-and-translationese-in","title":"Statistical Power and Translationese in Machine Translation Evaluation","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"tencent-ai-lab-machine-translation-systems","title":"Tencent AI Lab Machine Translation Systems for WMT20 Chat Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"tencent-neural-machine-translation-systems-1","title":"Tencent Neural Machine Translation Systems for the WMT20 News Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"tencent-submission-for-wmt20-quality","title":"Tencent submission for WMT20 Quality Estimation Shared Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"terminology-constrained-neural-machine","title":"Terminology-Constrained Neural Machine Translation at SAP","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-adapt-system-description-for-the-wmt20","title":"The ADAPT System Description for the WMT20 News Translation Task","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"d7834635f37e8049c58935797ded13cc48ec69464531af07fe785bab0cd7d5b1","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}