{"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/read-yaml-file","entry":"read_yaml_file","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":7,"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":7,"n_samples_ran":4,"n_samples_fingerprinted":0,"n_places":7,"n_places_pointer_only":4,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":3,"unverified":3},"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":"2409.04409","paper":"/paper/train-till-you-drop-towards-stable-and-robust","title":"Train Till You Drop: Towards Stable and Robust Source-free Unsupervised 3D Domain Adaptation","date":"2024-09-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"valeoai/ttyd","path":"configs_and_mappings.py","file_url":"https://github.com/valeoai/ttyd/blob/HEAD/configs_and_mappings.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"5db569379bf8e3f7","mcp_get_code":{"code_sha256":"5db569379bf8e3f7"}},{"arxiv_id":"2406.12546","paper":"/paper/liar-liar-logical-mire-a-benchmark-for","title":"Liar, Liar, Logical Mire: A Benchmark for Suppositional Reasoning in Large Language Models","date":"2024-06-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mainlp/TruthQuest","path":"metareasoning/utils/utils.py","file_url":"https://github.com/mainlp/TruthQuest/blob/HEAD/metareasoning/utils/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"CC-BY-SA-4.0","inline_ok":false,"code_sha256_prefix":"d05488b912cd3af0","mcp_get_code":{"code_sha256":"d05488b912cd3af0"}},{"arxiv_id":"2402.14856","paper":"/paper/comparing-inferential-strategies-of-humans","title":"Comparing Inferential Strategies of Humans and Large Language Models in Deductive Reasoning","date":"2024-02-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mainlp/inferential-strategies","path":"reasoning_strategies/utils/utils.py","file_url":"https://github.com/mainlp/inferential-strategies/blob/HEAD/reasoning_strategies/utils/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"CC-BY-SA-4.0","inline_ok":false,"code_sha256_prefix":"3f821e04d5d9a0fe","mcp_get_code":{"code_sha256":"3f821e04d5d9a0fe"}},{"arxiv_id":"2311.09071","paper":"/paper/how-multilingual-is-multilingual-llm","title":"How Vocabulary Sharing Facilitates Multilingualism in LLaMA?","date":"2023-11-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"cone-mt/vocabulary-sharing-facilitates-multilingualism","path":"Shorten/inference.py","file_url":"https://github.com/cone-mt/vocabulary-sharing-facilitates-multilingualism/blob/HEAD/Shorten/inference.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"9826ffe893c1e6a5","mcp_get_code":{"code_sha256":"9826ffe893c1e6a5"}},{"arxiv_id":"2305.14314","paper":"/paper/qlora-efficient-finetuning-of-quantized-llms","title":"QLoRA: Efficient Finetuning of Quantized LLMs","date":"2023-05-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"georgesung/llm_qlora","path":"inference.py","file_url":"https://github.com/georgesung/llm_qlora/blob/HEAD/inference.py","status":"ran_draft_wrong","verification_level":2,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"38a41485b6f05e08","mcp_get_code":{"code_sha256":"38a41485b6f05e08"}},{"arxiv_id":"2007.09548","paper":"/paper/kinematic-3d-object-detection-in-monocular","title":"Kinematic 3D Object Detection in Monocular Video","date":"2020-07-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Nicholasli1995/EgoNet","path":"libs/arguments/parse.py","file_url":"https://github.com/Nicholasli1995/EgoNet/blob/HEAD/libs/arguments/parse.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b4f9a04dd604efae","mcp_get_code":{"code_sha256":"b4f9a04dd604efae"}},{"arxiv_id":"2005.11079","paper":"/paper/graph-random-neural-network","title":"Graph Random Neural Network for Semi-Supervised Learning on Graphs","date":"2020-05-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"junzhuang-code/lindt","path":"src/utils.py","file_url":"https://github.com/junzhuang-code/lindt/blob/HEAD/src/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"50cce9ad0aedf824","mcp_get_code":{"code_sha256":"50cce9ad0aedf824"}}]}