{"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/encode-passages","entry":"encode_passages","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":10,"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":3,"n_samples_ran":3,"n_samples_fingerprinted":0,"n_places":10,"n_places_pointer_only":8,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":2,"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":"2410.05162","paper":"/paper/deciphering-the-interplay-of-parametric-and","title":"Deciphering the Interplay of Parametric and Non-parametric Memory in Retrieval-augmented Language Models","date":"2024-10-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"m3hrdadfi/rag-memory-interplay","path":"src/atlas/atlas.py","file_url":"https://github.com/m3hrdadfi/rag-memory-interplay/blob/HEAD/src/atlas/atlas.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":"e4a21bc7a716330c","mcp_get_code":{"code_sha256":"e4a21bc7a716330c"}},{"arxiv_id":"2410.04139","paper":"/paper/from-reading-to-compressing-exploring-the","title":"From Reading to Compressing: Exploring the Multi-document Reader for Prompt Compression","date":"2024-10-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"eunseongc/r2c","path":"src_fid/data.py","file_url":"https://github.com/eunseongc/r2c/blob/HEAD/src_fid/data.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"9410e388b51e48de","mcp_get_code":{"code_sha256":"9410e388b51e48de"}},{"arxiv_id":"2406.18847","paper":"/paper/learning-retrieval-augmentation-for","title":"Learning Retrieval Augmentation for Personalized Dialogue Generation","date":"2024-06-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"hqsiswiliam/lapdog","path":"src/lapdog.py","file_url":"https://github.com/hqsiswiliam/lapdog/blob/HEAD/src/lapdog.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":"e4a21bc7a716330c","mcp_get_code":{"code_sha256":"e4a21bc7a716330c"}},{"arxiv_id":"2402.05391","paper":"/paper/knowledge-graphs-meet-multi-modal-learning-a","title":"Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey","date":"2024-02-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"hackerchenzhuo/LaKo","path":"src/data.py","file_url":"https://github.com/hackerchenzhuo/LaKo/blob/HEAD/src/data.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bc0dae797248182b","mcp_get_code":{"code_sha256":"bc0dae797248182b"}},{"arxiv_id":"2402.02503","paper":"/paper/gerea-question-aware-prompt-captions-for","title":"GeReA: Question-Aware Prompt Captions for Knowledge-based Visual Question Answering","date":"2024-02-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"upper9527/gerea","path":"src/data.py","file_url":"https://github.com/upper9527/gerea/blob/HEAD/src/data.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"bc0dae797248182b","mcp_get_code":{"code_sha256":"bc0dae797248182b"}},{"arxiv_id":"2401.16979","paper":"/paper/re3val-reinforced-and-reranked-generative","title":"Re3val: Reinforced and Reranked Generative Retrieval","date":"2024-01-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"facebookresearch/FiD","path":"src/data.py","file_url":"https://github.com/facebookresearch/FiD/blob/HEAD/src/data.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"bc0dae797248182b","mcp_get_code":{"code_sha256":"bc0dae797248182b"}},{"arxiv_id":"2401.03568","paper":"/paper/agent-ai-surveying-the-horizons-of-multimodal","title":"Agent AI: Surveying the Horizons of Multimodal Interaction","date":"2024-01-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"guilk/kat","path":"src/data.py","file_url":"https://github.com/guilk/kat/blob/HEAD/src/data.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"bc0dae797248182b","mcp_get_code":{"code_sha256":"bc0dae797248182b"}},{"arxiv_id":"2308.07922","paper":"/paper/raven-in-context-learning-with-retrieval","title":"RAVEN: In-Context Learning with Retrieval-Augmented Encoder-Decoder Language Models","date":"2023-08-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jeffhj/raven","path":"src/atlas.py","file_url":"https://github.com/jeffhj/raven/blob/HEAD/src/atlas.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":"e4a21bc7a716330c","mcp_get_code":{"code_sha256":"e4a21bc7a716330c"}},{"arxiv_id":"2208.03299","paper":"/paper/few-shot-learning-with-retrieval-augmented","title":"Atlas: Few-shot Learning with Retrieval Augmented Language Models","date":"2022-08-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"facebookresearch/atlas","path":"src/atlas.py","file_url":"https://github.com/facebookresearch/atlas/blob/HEAD/src/atlas.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"e4a21bc7a716330c","mcp_get_code":{"code_sha256":"e4a21bc7a716330c"}},{"arxiv_id":"2112.08688","paper":"/paper/evidentiality-guided-generation-for-knowledge","title":"Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks","date":"2021-12-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"akariasai/evidentiality_qa","path":"evi_gen/src/data.py","file_url":"https://github.com/akariasai/evidentiality_qa/blob/HEAD/evi_gen/src/data.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"bc0dae797248182b","mcp_get_code":{"code_sha256":"bc0dae797248182b"}}]}