{"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/readfile-2","entry":"readFile","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":1,"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":1,"n_samples_fingerprinted":0,"n_places":6,"n_places_pointer_only":1,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"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":"2605.18133","paper":"/paper/arxiv-2605-18133","title":"An Empirical Study of Privacy Leakage Chains via Prompt Injection in Black-Box Chatbot Environments","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"In-Sam/Kill-Chain-of-Privacy-Leakage-via-Prompt-Injection","path":"prompt_injection/manipulate_settings.py","file_url":"https://github.com/In-Sam/Kill-Chain-of-Privacy-Leakage-via-Prompt-Injection/blob/HEAD/prompt_injection/manipulate_settings.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c51a7fa8a0047000","mcp_get_code":{"code_sha256":"c51a7fa8a0047000"}},{"arxiv_id":"2604.02520","paper":"/paper/arxiv-2604-02520","title":"Neural posterior estimation for scalable and accurate inverse parameter inference in Li-ion batteries","date":null,"month_inferred_from_arxiv_id":"2026-04","title_source":"syntology","repo":"NatLabRockies/BatFIT","path":"batfit/calibration/data_utils.py","file_url":"https://github.com/NatLabRockies/BatFIT/blob/HEAD/batfit/calibration/data_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"749f14f18ac3a486","mcp_get_code":{"code_sha256":"749f14f18ac3a486"}},{"arxiv_id":"2204.05798","paper":"/paper/multi-view-breast-cancer-classification-via","title":"Multi-View Hypercomplex Learning for Breast Cancer Screening","date":"2022-04-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ispamm/phbreast","path":"utils/readFile.py","file_url":"https://github.com/ispamm/phbreast/blob/HEAD/utils/readFile.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"519e9cfd9abb2442","mcp_get_code":{"code_sha256":"519e9cfd9abb2442"}},{"arxiv_id":"1803.06815","paper":"/paper/espnet-efficient-spatial-pyramid-of-dilated","title":"ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation","date":"2018-03-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"simuler/ESPNet","path":"compute_classweight.py","file_url":"https://github.com/simuler/ESPNet/blob/HEAD/compute_classweight.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":"9c1bd7a7658cc12c","mcp_get_code":{"code_sha256":"9c1bd7a7658cc12c"}},{"arxiv_id":"1511.05298","paper":"/paper/structural-rnn-deep-learning-on-spatio","title":"Structural-RNN: Deep Learning on Spatio-Temporal Graphs","date":"2015-11-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhaolongkzz/human_motion","path":"scripts/Animation/motionAnimation.py","file_url":"https://github.com/zhaolongkzz/human_motion/blob/HEAD/scripts/Animation/motionAnimation.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"e767841ab10a369a","mcp_get_code":{"code_sha256":"e767841ab10a369a"}},{"arxiv_id":"1507.05717","paper":"/paper/an-end-to-end-trainable-neural-network-for","title":"An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition","date":"2015-07-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"nithyadurai87/pottan-ocr-tamil","path":"pottan_ocr/utils.py","file_url":"https://github.com/nithyadurai87/pottan-ocr-tamil/blob/HEAD/pottan_ocr/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"1d4c2738c60c2109","mcp_get_code":{"code_sha256":"1d4c2738c60c2109"}}]}