{"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/average-distributed-scalar","entry":"average_distributed_scalar","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":5,"n_papers_ran":4,"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":2,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":3,"by_status":{"ran_honours":1,"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":"2310.15896","paper":"/paper/bianque-balancing-the-questioning-and","title":"BianQue: Balancing the Questioning and Suggestion Ability of Health LLMs with Multi-turn Health Conversations Polished by ChatGPT","date":"2023-10-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"scutcyr/bianque","path":"train_model.py","file_url":"https://github.com/scutcyr/bianque/blob/HEAD/train_model.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"ebb24f4dc2a81286","mcp_get_code":{"code_sha256":"ebb24f4dc2a81286"}},{"arxiv_id":"2009.12005","paper":"/paper/mintl-minimalist-transfer-learning-for-task","title":"MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems","date":"2020-09-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zlinao/MinTL","path":"pretraining.py","file_url":"https://github.com/zlinao/MinTL/blob/HEAD/pretraining.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ebb24f4dc2a81286","mcp_get_code":{"code_sha256":"ebb24f4dc2a81286"}},{"arxiv_id":"2008.09075","paper":"/paper/controlling-dialogue-generation-with-semantic","title":"Controlling Dialogue Generation with Semantic Exemplars","date":"2020-08-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":null,"path":"","file_url":null,"status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"code_sha256_prefix":"ebb24f4dc2a81286","mcp_get_code":{"code_sha256":"ebb24f4dc2a81286"}},{"arxiv_id":"1901.08149","paper":"/paper/transfertransfo-a-transfer-learning-approach","title":"TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents","date":"2019-01-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dladustn95/ENMODEL","path":"bertTran_train.py","file_url":"https://github.com/dladustn95/ENMODEL/blob/HEAD/bertTran_train.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"ebb24f4dc2a81286","mcp_get_code":{"code_sha256":"ebb24f4dc2a81286"}},{"arxiv_id":"2022.emnlp-industry.44","paper":null,"title":"arXiv:2022.emnlp-industry.44","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"VectorInstitute/NAA","path":"responsegeneration/utils.py","file_url":"https://github.com/VectorInstitute/NAA/blob/HEAD/responsegeneration/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"aab459ddf1cf9850","mcp_get_code":{"code_sha256":"aab459ddf1cf9850"}}]}