{"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-manifest","entry":"read_manifest","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":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":6,"n_samples_ran":3,"n_samples_fingerprinted":0,"n_places":6,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"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":"2606.13662","paper":"/paper/arxiv-2606-13662","title":"EurekAgent: Agent Environment Engineering is All You Need For Autonomous Scientific Discovery","date":null,"month_inferred_from_arxiv_id":"2026-06","title_source":"syntology","repo":"THU-Team-Eureka/EurekAgent","path":"src/history.py","file_url":"https://github.com/THU-Team-Eureka/EurekAgent/blob/HEAD/src/history.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"AGPL-3.0","inline_ok":false,"code_sha256_prefix":"d0d06b9acae3daec","mcp_get_code":{"code_sha256":"d0d06b9acae3daec"}},{"arxiv_id":"2606.09930","paper":"/paper/arxiv-2606-09930","title":"Compile Once, Differentiate Everywhere: A Differentiable Meta-Circular Interpreter","date":null,"month_inferred_from_arxiv_id":"2026-06","title_source":"syntology","repo":"sheneman/dmci","path":"experiments/check_manifests.py","file_url":"https://github.com/sheneman/dmci/blob/HEAD/experiments/check_manifests.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ad5da3ef9764d7ec","mcp_get_code":{"code_sha256":"ad5da3ef9764d7ec"}},{"arxiv_id":"2602.03024","paper":"/paper/arxiv-2602-03024","title":"Consistency Deep Equilibrium Models","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"landrarwolf/CDEQ","path":"CLLM-src/llm_cdeq/cache.py","file_url":"https://github.com/landrarwolf/CDEQ/blob/HEAD/CLLM-src/llm_cdeq/cache.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"1a5025436f52b641","mcp_get_code":{"code_sha256":"1a5025436f52b641"}},{"arxiv_id":"2511.21522","paper":"/paper/arxiv-2511-21522","title":"Pessimistic Verification for Open-Ended Math Questions","date":null,"month_inferred_from_arxiv_id":"2025-11","title_source":"syntology","repo":"THUNLP-MT/pverify","path":"utils/arxiv_bench.py","file_url":"https://github.com/THUNLP-MT/pverify/blob/HEAD/utils/arxiv_bench.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a2f0bac6c3ebfb01","mcp_get_code":{"code_sha256":"a2f0bac6c3ebfb01"}},{"arxiv_id":"2410.00025","paper":"/paper/improving-spoken-language-modeling-with","title":"Improving Spoken Language Modeling with Phoneme Classification: A Simple Fine-tuning Approach","date":"2024-09-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"bootphon/spokenlm-phoneme","path":"src/phonslm/reader.py","file_url":"https://github.com/bootphon/spokenlm-phoneme/blob/HEAD/src/phonslm/reader.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"5ba01378940cd9b8","mcp_get_code":{"code_sha256":"5ba01378940cd9b8"}},{"arxiv_id":"aaai_32078","paper":null,"title":"arXiv:aaai_32078","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"YifanZhang-git/SKAPP","path":"src/datasets.py","file_url":"https://github.com/YifanZhang-git/SKAPP/blob/HEAD/src/datasets.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bb619ee43988e9c7","mcp_get_code":{"code_sha256":"bb619ee43988e9c7"}}]}