{"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-total-len","entry":"get_total_len","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":6,"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":1,"n_samples_fingerprinted":1,"n_places":6,"n_places_pointer_only":3,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"unverified":0},"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":"2605.21539","paper":"/paper/arxiv-2605-21539","title":"DualOptim+: Bridging Shared and Decoupled Optimizer States for Better Machine Unlearning in Large Language Models","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"CityU-MLO/DualOptimPlus","path":"utils/utils.py","file_url":"https://github.com/CityU-MLO/DualOptimPlus/blob/HEAD/utils/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"6c542acea5aa211c","mcp_get_code":{"code_sha256":"6c542acea5aa211c"}},{"arxiv_id":"2410.08109","paper":"/paper/a-closer-look-at-machine-unlearning-for-large","title":"A Closer Look at Machine Unlearning for Large Language Models","date":"2024-10-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sail-sg/closer-look-LLM-unlearning","path":"utils/utils.py","file_url":"https://github.com/sail-sg/closer-look-LLM-unlearning/blob/HEAD/utils/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"6c542acea5aa211c","mcp_get_code":{"code_sha256":"6c542acea5aa211c"}},{"arxiv_id":"2406.13356","paper":"/paper/jogging-the-memory-of-unlearned-model-through","title":"Jogging the Memory of Unlearned LLMs Through Targeted Relearning Attacks","date":"2024-06-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"s-huu/jog_llm_memory","path":"synthetic/utils.py","file_url":"https://github.com/s-huu/jog_llm_memory/blob/HEAD/synthetic/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"6c542acea5aa211c","mcp_get_code":{"code_sha256":"6c542acea5aa211c"}},{"arxiv_id":"2406.11614","paper":"/paper/intrinsic-evaluation-of-unlearning-using","title":"Intrinsic Evaluation of Unlearning Using Parametric Knowledge Traces","date":"2024-06-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yihuaihong/conceptvectors","path":"utils.py","file_url":"https://github.com/yihuaihong/conceptvectors/blob/HEAD/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"CC-BY-4.0","inline_ok":false,"code_sha256_prefix":"6c542acea5aa211c","mcp_get_code":{"code_sha256":"6c542acea5aa211c"}},{"arxiv_id":"2401.06121","paper":"/paper/tofu-a-task-of-fictitious-unlearning-for-llms","title":"TOFU: A Task of Fictitious Unlearning for LLMs","date":"2024-01-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"locuslab/tofu","path":"utils.py","file_url":"https://github.com/locuslab/tofu/blob/HEAD/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"6c542acea5aa211c","mcp_get_code":{"code_sha256":"6c542acea5aa211c"}},{"arxiv_id":"2025.findings-acl.949","paper":null,"title":"arXiv:2025.findings-acl.949","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"renjie3/GRUN","path":"baseline/utils.py","file_url":"https://github.com/renjie3/GRUN/blob/HEAD/baseline/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"6c542acea5aa211c","mcp_get_code":{"code_sha256":"6c542acea5aa211c"}}]}