{"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/save-result","entry":"save_result","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":10,"n_papers_ran":5,"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":8,"n_samples_ran":3,"n_samples_fingerprinted":0,"n_places":10,"n_places_pointer_only":6,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":1,"ran":1,"unverified":5},"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":"2412.17596","paper":"/paper/liveideabench-evaluating-llms-scientific","title":"LiveIdeaBench: Evaluating LLMs' Scientific Creativity and Idea Generation with Minimal Context","date":"2024-12-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"x66ccff/liveideabench","path":"utils/database.py","file_url":"https://github.com/x66ccff/liveideabench/blob/HEAD/utils/database.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"8344c18f6c6bbafd","mcp_get_code":{"code_sha256":"8344c18f6c6bbafd"}},{"arxiv_id":"2412.09501","paper":"/paper/lyra-an-efficient-and-speech-centric","title":"Lyra: An Efficient and Speech-Centric Framework for Omni-Cognition","date":"2024-12-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dvlab-research/Lyra","path":"lyra/eval/model_lyra_text_speech.py","file_url":"https://github.com/dvlab-research/Lyra/blob/HEAD/lyra/eval/model_lyra_text_speech.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"7719de171ef38b85","mcp_get_code":{"code_sha256":"7719de171ef38b85"}},{"arxiv_id":"2411.14717","paper":"/paper/fedmllm-federated-fine-tuning-mllm-on","title":"FedMLLM: Federated Fine-tuning MLLM on Multimodal Heterogeneity Data","date":"2024-11-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"1xbq1/fedmllm","path":"eval_medical.py","file_url":"https://github.com/1xbq1/fedmllm/blob/HEAD/eval_medical.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"32f8f1bcb6c46c13","mcp_get_code":{"code_sha256":"32f8f1bcb6c46c13"}},{"arxiv_id":"2405.10311","paper":"/paper/unirag-universal-retrieval-augmentation-for","title":"UniRAG: Universal Retrieval Augmentation for Large Vision Language Models","date":"2024-05-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"castorini/unirag","path":"src/unirag/utils.py","file_url":"https://github.com/castorini/unirag/blob/HEAD/src/unirag/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"58629c6a6cb6b282","mcp_get_code":{"code_sha256":"58629c6a6cb6b282"}},{"arxiv_id":"2403.11186","paper":"/paper/nettrack-tracking-highly-dynamic-objects-with","title":"NetTrack: Tracking Highly Dynamic Objects with a Net","date":"2024-03-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"George-Zhuang/NetTrack","path":"tracker/nettrack.py","file_url":"https://github.com/George-Zhuang/NetTrack/blob/HEAD/tracker/nettrack.py","status":"ran_fixture","verification_level":1,"contract_check":"DEP_MISSING","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"7aafbf95486fb2c0","mcp_get_code":{"code_sha256":"7aafbf95486fb2c0"}},{"arxiv_id":"2402.03161","paper":"/paper/video-lavit-unified-video-language-pre","title":"Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization","date":"2024-02-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jy0205/lavit","path":"LaVIT/utils.py","file_url":"https://github.com/jy0205/lavit/blob/HEAD/LaVIT/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"58629c6a6cb6b282","mcp_get_code":{"code_sha256":"58629c6a6cb6b282"}},{"arxiv_id":"2211.10797","paper":"/paper/an-empirical-study-on-contrastive-search-and","title":"An Empirical Study On Contrastive Search And Contrastive Decoding For Open-ended Text Generation","date":"2022-11-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":null,"path":"","file_url":null,"status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"code_sha256_prefix":"08a4d22e5a9f3b60","mcp_get_code":{"code_sha256":"08a4d22e5a9f3b60"}},{"arxiv_id":"2210.14140","paper":"/paper/contrastive-search-is-what-you-need-for","title":"Contrastive Search Is What You Need For Neural Text Generation","date":"2022-10-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yxuansu/contrastive_search_is_what_you_need","path":"code_generation/inference.py","file_url":"https://github.com/yxuansu/contrastive_search_is_what_you_need/blob/HEAD/code_generation/inference.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"08a4d22e5a9f3b60","mcp_get_code":{"code_sha256":"08a4d22e5a9f3b60"}},{"arxiv_id":"2108.00146","paper":"/paper/t-k-ml-ap-adversarial-attacks-to-top-k-multi","title":"T$_k$ML-AP: Adversarial Attacks to Top-$k$ Multi-Label Learning","date":"2021-07-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"discovershu/TKML-AP","path":"attack.py","file_url":"https://github.com/discovershu/TKML-AP/blob/HEAD/attack.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c3197cc1dc16ced8","mcp_get_code":{"code_sha256":"c3197cc1dc16ced8"}},{"arxiv_id":"2105.01051","paper":"/paper/superb-speech-processing-universal","title":"SUPERB: Speech processing Universal PERformance Benchmark","date":"2021-05-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"usc-sail/fed-ser-leakage","path":"mitigation/federated_ser_classifier_udp.py","file_url":"https://github.com/usc-sail/fed-ser-leakage/blob/HEAD/mitigation/federated_ser_classifier_udp.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fbdf6d939f822660","mcp_get_code":{"code_sha256":"fbdf6d939f822660"}}]}