{"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/remove-urls","entry":"remove_urls","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":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":6,"n_samples_ran":4,"n_samples_fingerprinted":3,"n_places":6,"n_places_pointer_only":0,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":4,"unverified":2},"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":"2506.11763","paper":"/paper/deepresearch-bench-a-comprehensive-benchmark","title":"DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents","date":"2025-06-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ayanami0730/deep_research_bench","path":"utils/extract.py","file_url":"https://github.com/ayanami0730/deep_research_bench/blob/HEAD/utils/extract.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":"6f329652e5b07a90","mcp_get_code":{"code_sha256":"6f329652e5b07a90"}},{"arxiv_id":"2410.13098","paper":"/paper/a-little-human-data-goes-a-long-way","title":"A Little Human Data Goes A Long Way","date":"2024-10-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dhananjayashok/littlehumandata","path":"prompt_generation/prompt_models.py","file_url":"https://github.com/dhananjayashok/littlehumandata/blob/HEAD/prompt_generation/prompt_models.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b726f185fd16d31d","mcp_get_code":{"code_sha256":"b726f185fd16d31d"}},{"arxiv_id":"2402.06221","paper":"/paper/resumeflow-an-llm-facilitated-pipeline-for","title":"ResumeFlow: An LLM-facilitated Pipeline for Personalized Resume Generation and Refinement","date":"2024-02-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Ztrimus/job-llm","path":"zlm/utils/metrics.py","file_url":"https://github.com/Ztrimus/job-llm/blob/HEAD/zlm/utils/metrics.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"38d213c5cd66f679","mcp_get_code":{"code_sha256":"38d213c5cd66f679"}},{"arxiv_id":"2308.09055","paper":"/paper/don-t-lose-the-message-while-paraphrasing-a","title":"Don't lose the message while paraphrasing: A study on content preserving style transfer","date":"2023-08-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"s-nlp/lewit-informal","path":"lewip_informal/utils.py","file_url":"https://github.com/s-nlp/lewit-informal/blob/HEAD/lewip_informal/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":"1ce6f12c5252b26e","mcp_get_code":{"code_sha256":"1ce6f12c5252b26e"}},{"arxiv_id":"2308.02976","paper":"/paper/spanish-pre-trained-bert-model-and-evaluation","title":"Spanish Pre-trained BERT Model and Evaluation Data","date":"2023-08-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"josecannete/spanish-corpora","path":"corpus_processing.py","file_url":"https://github.com/josecannete/spanish-corpora/blob/HEAD/corpus_processing.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"63582c062b86a49d","mcp_get_code":{"code_sha256":"63582c062b86a49d"}},{"arxiv_id":"2209.13773","paper":"/paper/mets-cov-a-dataset-of-medical-entity-and","title":"METS-CoV: A Dataset of Medical Entity and Targeted Sentiment on COVID-19 Related Tweets","date":"2022-09-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ylab-open/mets-cov","path":"preprocess.py","file_url":"https://github.com/ylab-open/mets-cov/blob/HEAD/preprocess.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":"db52d0b43e015710","mcp_get_code":{"code_sha256":"db52d0b43e015710"}}]}