{"about":{"site":"https://codewithpapers.app","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.","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"},"url":"/code/seq2seq","entry":"Seq2Seq","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":6,"n_papers_ran":3,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":12,"n_samples_ran":5,"n_samples_fingerprinted":0,"n_places":12,"n_places_pointer_only":8,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":5,"unverified":7},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2109.00859","paper":"/paper/codet5-identifier-aware-unified-pre-trained","title":"CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation","date":"2021-09-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"salesforce/CodeT5","path":"CodeT5/models.py","file_url":"https://github.com/salesforce/CodeT5/blob/HEAD/CodeT5/models.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"fde59ee6f478c51c","mcp_get_code":{"code_sha256":"fde59ee6f478c51c"}},{"arxiv_id":"2002.08155","paper":"/paper/codebert-a-pre-trained-model-for-programming","title":"CodeBERT: A Pre-Trained Model for Programming and Natural Languages","date":"2020-02-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zfj1998/CodeBert-Code2Text","path":"code/model.py","file_url":"https://github.com/zfj1998/CodeBert-Code2Text/blob/HEAD/code/model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"09b02d6c43ccfaa8","mcp_get_code":{"code_sha256":"09b02d6c43ccfaa8"}},{"arxiv_id":"2002.08155","paper":"/paper/codebert-a-pre-trained-model-for-programming","title":"CodeBERT: A Pre-Trained Model for Programming and Natural Languages","date":"2020-02-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"microsoft/CodeBERT","path":"CodeBERT/code2nl/model.py","file_url":"https://github.com/microsoft/CodeBERT/blob/HEAD/CodeBERT/code2nl/model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"8053f41db1d56bde","mcp_get_code":{"code_sha256":"8053f41db1d56bde"}},{"arxiv_id":"1706.03762","paper":"/paper/attention-is-all-you-need","title":"Attention Is All You Need","date":"2017-06-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"akashe/Python-Code-Generation","path":"model.py","file_url":"https://github.com/akashe/Python-Code-Generation/blob/HEAD/model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"dfb9c8f444a9dc01","mcp_get_code":{"code_sha256":"dfb9c8f444a9dc01"}},{"arxiv_id":"1706.03762","paper":"/paper/attention-is-all-you-need","title":"Attention Is All You Need","date":"2017-06-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Andrey885/Machine_translation_PyTorch","path":"models.py","file_url":"https://github.com/Andrey885/Machine_translation_PyTorch/blob/HEAD/models.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"7e9440e2c269d7f8","mcp_get_code":{"code_sha256":"7e9440e2c269d7f8"}},{"arxiv_id":"1706.03762","paper":"/paper/attention-is-all-you-need","title":"Attention Is All You Need","date":"2017-06-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"monimoyd/NLPEnglishToPythonCodeUsingTransformer","path":"models/english_to_python_transformer.py","file_url":"https://github.com/monimoyd/NLPEnglishToPythonCodeUsingTransformer/blob/HEAD/models/english_to_python_transformer.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"dcb26e722b558f56","mcp_get_code":{"code_sha256":"dcb26e722b558f56"}},{"arxiv_id":"1609.08144","paper":"/paper/googles-neural-machine-translation-system","title":"Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation","date":"2016-09-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ZHANG45/multi_gpu_seq2seq","path":"seq2seq2.py","file_url":"https://github.com/ZHANG45/multi_gpu_seq2seq/blob/HEAD/seq2seq2.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"92bf320d3ebcecdb","mcp_get_code":{"code_sha256":"92bf320d3ebcecdb"}},{"arxiv_id":"1609.08144","paper":"/paper/googles-neural-machine-translation-system","title":"Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation","date":"2016-09-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"kh-kim/simple-nmt","path":"simple_nmt/models/seq2seq.py","file_url":"https://github.com/kh-kim/simple-nmt/blob/HEAD/simple_nmt/models/seq2seq.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"14b02b13476db551","mcp_get_code":{"code_sha256":"14b02b13476db551"}},{"arxiv_id":"1406.1078","paper":"/paper/learning-phrase-representations-using-rnn","title":"Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation","date":"2014-06-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Nick-Zhao-Engr/Machine-Translation","path":"hannmtModel/HANNMT/compare/1_RNN_Encoder-Decoder_for_SMT.py","file_url":"https://github.com/Nick-Zhao-Engr/Machine-Translation/blob/HEAD/hannmtModel/HANNMT/compare/1_RNN_Encoder-Decoder_for_SMT.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"97aaf6f5558112f8","mcp_get_code":{"code_sha256":"97aaf6f5558112f8"}},{"arxiv_id":"1406.1078","paper":"/paper/learning-phrase-representations-using-rnn","title":"Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation","date":"2014-06-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"littleflow3r/Japanese_English_Machine_Translation_Seq2Seq","path":"model.py","file_url":"https://github.com/littleflow3r/Japanese_English_Machine_Translation_Seq2Seq/blob/HEAD/model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c1747f21ffe18473","mcp_get_code":{"code_sha256":"c1747f21ffe18473"}},{"arxiv_id":"1406.1078","paper":"/paper/learning-phrase-representations-using-rnn","title":"Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation","date":"2014-06-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"graykode/nlp-tutorial","path":"4-1.Seq2Seq/Seq2Seq.py","file_url":"https://github.com/graykode/nlp-tutorial/blob/HEAD/4-1.Seq2Seq/Seq2Seq.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"0e85857408d20491","mcp_get_code":{"code_sha256":"0e85857408d20491"}},{"arxiv_id":"2023.findings-emnlp.4","paper":null,"title":"arXiv:2023.findings-emnlp.4","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"AI4Bharat/IndicXlit","path":"app/ai4bharat/transliteration/rnn/core.py","file_url":"https://github.com/AI4Bharat/IndicXlit/blob/HEAD/app/ai4bharat/transliteration/rnn/core.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"643c13c8fa3c7dcc","mcp_get_code":{"code_sha256":"643c13c8fa3c7dcc"}}]}