{"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/import-params","entry":"import_params","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":9,"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":5,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":14,"n_places_pointer_only":0,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":0,"unverified":4},"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":"2212.09387","paper":"/paper/prompt-gating-a-parameter-efficient-tuning","title":"An Extensible Plug-and-Play Method for Multi-Aspect Controllable Text Generation","date":"2022-12-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"thunlp-mt/promptgating4mctg","path":"codes/thumt/bin/scorer.py","file_url":"https://github.com/thunlp-mt/promptgating4mctg/blob/HEAD/codes/thumt/bin/scorer.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":"40ababf4a5b7509f","mcp_get_code":{"code_sha256":"40ababf4a5b7509f"}},{"arxiv_id":"2205.03766","paper":"/paper/scheduled-multi-task-learning-for-neural-chat","title":"Scheduled Multi-task Learning for Neural Chat Translation","date":"2022-05-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"xl2248/sml","path":"thumt-sml/thumt/bin/scorer.py","file_url":"https://github.com/xl2248/sml/blob/HEAD/thumt-sml/thumt/bin/scorer.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"149a90364d6911d9","mcp_get_code":{"code_sha256":"149a90364d6911d9"}},{"arxiv_id":"2110.06609","paper":"/paper/msp-multi-stage-prompting-for-making-pre","title":"MSP: Multi-Stage Prompting for Making Pre-trained Language Models Better Translators","date":"2021-10-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"thunlp-mt/plm4mt","path":"thumt/bin/trainer.py","file_url":"https://github.com/thunlp-mt/plm4mt/blob/HEAD/thumt/bin/trainer.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"bb55d10bc8ee2bfa","mcp_get_code":{"code_sha256":"bb55d10bc8ee2bfa"}},{"arxiv_id":"2110.06609","paper":"/paper/msp-multi-stage-prompting-for-making-pre","title":"MSP: Multi-Stage Prompting for Making Pre-trained Language Models Better Translators","date":"2021-10-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"thunlp-mt/plm4mt","path":"thumt/bin/translator.py","file_url":"https://github.com/thunlp-mt/plm4mt/blob/HEAD/thumt/bin/translator.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":"da8001b0f721ab57","mcp_get_code":{"code_sha256":"da8001b0f721ab57"}},{"arxiv_id":"1901.04112","paper":"/paper/unsupervised-neural-machine-translation-with","title":"Unsupervised Neural Machine Translation with SMT as Posterior Regularization","date":"2019-01-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Imagist-Shuo/UNMT-SPR","path":"t2tlight/score.py","file_url":"https://github.com/Imagist-Shuo/UNMT-SPR/blob/HEAD/t2tlight/score.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"149a90364d6911d9","mcp_get_code":{"code_sha256":"149a90364d6911d9"}},{"arxiv_id":"1810.03581","paper":"/paper/improving-the-transformer-translation-model","title":"Improving the Transformer Translation Model with Document-Level Context","date":"2018-10-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Glaceon31/Document-Transformer","path":"thumt/bin/scorer.py","file_url":"https://github.com/Glaceon31/Document-Transformer/blob/HEAD/thumt/bin/scorer.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":"149a90364d6911d9","mcp_get_code":{"code_sha256":"149a90364d6911d9"}},{"arxiv_id":"1810.03581","paper":"/paper/improving-the-transformer-translation-model","title":"Improving the Transformer Translation Model with Document-Level Context","date":"2018-10-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Glaceon31/Document-Transformer","path":"thumt/bin/trainer.py","file_url":"https://github.com/Glaceon31/Document-Transformer/blob/HEAD/thumt/bin/trainer.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":"ba3612d14359b1ea","mcp_get_code":{"code_sha256":"ba3612d14359b1ea"}},{"arxiv_id":"1805.00631","paper":"/paper/accelerating-neural-transformer-via-an","title":"Accelerating Neural Transformer via an Average Attention Network","date":"2018-05-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"bzhangXMU/transformer-aan","path":"code/translator.py","file_url":"https://github.com/bzhangXMU/transformer-aan/blob/HEAD/code/translator.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":"149a90364d6911d9","mcp_get_code":{"code_sha256":"149a90364d6911d9"}},{"arxiv_id":"1805.00631","paper":"/paper/accelerating-neural-transformer-via-an","title":"Accelerating Neural Transformer via an Average Attention Network","date":"2018-05-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"bzhangXMU/transformer-aan","path":"code/trainer.py","file_url":"https://github.com/bzhangXMU/transformer-aan/blob/HEAD/code/trainer.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":"ba3612d14359b1ea","mcp_get_code":{"code_sha256":"ba3612d14359b1ea"}},{"arxiv_id":"1409.0473","paper":"/paper/neural-machine-translation-by-jointly","title":"Neural Machine Translation by Jointly Learning to Align and Translate","date":"2014-09-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"thunlp-mt/ckd","path":"thumt/bin/trainer.py","file_url":"https://github.com/thunlp-mt/ckd/blob/HEAD/thumt/bin/trainer.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"bb55d10bc8ee2bfa","mcp_get_code":{"code_sha256":"bb55d10bc8ee2bfa"}},{"arxiv_id":"2022.findings-acl.203","paper":null,"title":"arXiv:2022.findings-acl.203","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"yafuly/PromptNMT","path":"thumt/bin/trainer.py","file_url":"https://github.com/yafuly/PromptNMT/blob/HEAD/thumt/bin/trainer.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"bb55d10bc8ee2bfa","mcp_get_code":{"code_sha256":"bb55d10bc8ee2bfa"}},{"arxiv_id":"2022.findings-acl.203","paper":null,"title":"arXiv:2022.findings-acl.203","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"yafuly/PromptNMT","path":"thumt/bin/scorer.py","file_url":"https://github.com/yafuly/PromptNMT/blob/HEAD/thumt/bin/scorer.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":"40ababf4a5b7509f","mcp_get_code":{"code_sha256":"40ababf4a5b7509f"}},{"arxiv_id":"2022.findings-acl.203","paper":null,"title":"arXiv:2022.findings-acl.203","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"yafuly/PromptNMT","path":"thumt/bin/translator.py","file_url":"https://github.com/yafuly/PromptNMT/blob/HEAD/thumt/bin/translator.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":"da8001b0f721ab57","mcp_get_code":{"code_sha256":"da8001b0f721ab57"}},{"arxiv_id":"2020.acl-main.320","paper":null,"title":"arXiv:2020.acl-main.320","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"Imagist-Shuo/RRforUNMT","path":"unsupMT/NMT_code/score.py","file_url":"https://github.com/Imagist-Shuo/RRforUNMT/blob/HEAD/unsupMT/NMT_code/score.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"149a90364d6911d9","mcp_get_code":{"code_sha256":"149a90364d6911d9"}}]}