{"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/get-next-version","entry":"get_next_version","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":13,"n_papers_ran":0,"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":1,"n_samples_ran":0,"n_samples_fingerprinted":0,"n_places":13,"n_places_pointer_only":7,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":0,"unverified":1},"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":"2406.03878","paper":"/paper/decoder-only-streaming-transformer-for","title":"Decoder-only Streaming Transformer for Simultaneous Translation","date":"2024-06-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ictnlp/DST","path":"release_utils.py","file_url":"https://github.com/ictnlp/DST/blob/HEAD/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}},{"arxiv_id":"2405.18906","paper":"/paper/language-generation-with-strictly-proper","title":"Language Generation with Strictly Proper Scoring Rules","date":"2024-05-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"shaochenze/scoringruleslm","path":"release_utils.py","file_url":"https://github.com/shaochenze/scoringruleslm/blob/HEAD/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}},{"arxiv_id":"2403.01479","paper":"/paper/align-to-distill-trainable-attention","title":"Align-to-Distill: Trainable Attention Alignment for Knowledge Distillation in Neural Machine Translation","date":"2024-03-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ncsoft/Align-to-Distill","path":"release_utils.py","file_url":"https://github.com/ncsoft/Align-to-Distill/blob/HEAD/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}},{"arxiv_id":"2402.01404","paper":"/paper/on-measuring-context-utilization-in-document","title":"On Measuring Context Utilization in Document-Level MT Systems","date":"2024-02-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Wafaa014/context-utilization","path":"fairseq/release_utils.py","file_url":"https://github.com/Wafaa014/context-utilization/blob/HEAD/fairseq/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}},{"arxiv_id":"2305.17190","paper":"/paper/multiplication-free-transformer-training-via-1","title":"Multiplication-Free Transformer Training via Piecewise Affine Operations","date":"2023-05-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"epfml/piecewise-affine-multiplication","path":"submodules/fairseq/release_utils.py","file_url":"https://github.com/epfml/piecewise-affine-multiplication/blob/HEAD/submodules/fairseq/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}},{"arxiv_id":"2210.02592","paper":"/paper/ccc-wav2vec-2-0-clustering-aided-cross","title":"CCC-wav2vec 2.0: Clustering aided Cross Contrastive Self-supervised learning of speech representations","date":"2022-10-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"speech-lab-iitm/ccc-wav2vec-2.0","path":"release_utils.py","file_url":"https://github.com/speech-lab-iitm/ccc-wav2vec-2.0/blob/HEAD/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":false,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}},{"arxiv_id":"1907.06616","paper":"/paper/facebook-fairs-wmt19-news-translation-task","title":"Facebook FAIR's WMT19 News Translation Task Submission","date":"2019-07-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"cyberagentailab/mbr-anomaly","path":"fairseq/release_utils.py","file_url":"https://github.com/cyberagentailab/mbr-anomaly/blob/HEAD/fairseq/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}},{"arxiv_id":"2023.findings-emnlp.978","paper":null,"title":"arXiv:2023.findings-emnlp.978","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"libeineu/MMT-VQA","path":"release_utils.py","file_url":"https://github.com/libeineu/MMT-VQA/blob/HEAD/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}},{"arxiv_id":"2023.findings-emnlp.414","paper":null,"title":"arXiv:2023.findings-emnlp.414","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"WenbiaoYin/FuseST","path":"release_utils.py","file_url":"https://github.com/WenbiaoYin/FuseST/blob/HEAD/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":false,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}},{"arxiv_id":"2023.findings-emnlp.1045","paper":null,"title":"arXiv:2023.findings-emnlp.1045","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"xl8-ai/WordSiMT","path":"release_utils.py","file_url":"https://github.com/xl8-ai/WordSiMT/blob/HEAD/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":false,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}},{"arxiv_id":"2023.acl-long.751","paper":null,"title":"arXiv:2023.acl-long.751","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"lishangjie1/PEIT","path":"release_utils.py","file_url":"https://github.com/lishangjie1/PEIT/blob/HEAD/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":false,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}},{"arxiv_id":"2023.acl-long.380","paper":null,"title":"arXiv:2023.acl-long.380","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"li-aolong/TemplateGEC","path":"fairseq-0.12.2/release_utils.py","file_url":"https://github.com/li-aolong/TemplateGEC/blob/HEAD/fairseq-0.12.2/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}},{"arxiv_id":"2022.emnlp-main.663","paper":null,"title":"arXiv:2022.emnlp-main.663","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"mcao516/rej-summ","path":"release_utils.py","file_url":"https://github.com/mcao516/rej-summ/blob/HEAD/release_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":false,"code_sha256_prefix":"44b6e8848744468f","mcp_get_code":{"code_sha256":"44b6e8848744468f"}}]}