{"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/get-image-files","entry":"get_image_files","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":5,"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":5,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"unverified":4},"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":"2605.12138","paper":"/paper/arxiv-2605-12138","title":"Design Your Ad: Personalized Advertising Image and Text Generation with Unified Autoregressive Models","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"JD-GenX/Uni-AdGen","path":"PBS_metrics/convert_images_to_base64.py","file_url":"https://github.com/JD-GenX/Uni-AdGen/blob/HEAD/PBS_metrics/convert_images_to_base64.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"00a0e44046e8b797","mcp_get_code":{"code_sha256":"00a0e44046e8b797"}},{"arxiv_id":"2602.13286","paper":"/paper/arxiv-2602-13286","title":"Explanatory Interactive Machine Learning for Bias Mitigation in Visual Gender Classification","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"fhstp/xil-gender-classification","path":"explanatory_gender_classification/verify_data.py","file_url":"https://github.com/fhstp/xil-gender-classification/blob/HEAD/explanatory_gender_classification/verify_data.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"GPL-3.0","inline_ok":false,"code_sha256_prefix":"e6e872965a1589c0","mcp_get_code":{"code_sha256":"e6e872965a1589c0"}},{"arxiv_id":"2504.19373","paper":"/paper/doxing-via-the-lens-revealing-privacy-leakage","title":"Doxing via the Lens: Revealing Location-related Privacy Leakage on Multi-modal Large Reasoning Models","date":"2025-04-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"SaFo-Lab/DoxBench","path":"code/data_process/image_match_overwrite.py","file_url":"https://github.com/SaFo-Lab/DoxBench/blob/HEAD/code/data_process/image_match_overwrite.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":"733bfc936cbbf530","mcp_get_code":{"code_sha256":"733bfc936cbbf530"}},{"arxiv_id":"2406.09988","paper":"/paper/details-make-a-difference-object-state","title":"Details Make a Difference: Object State-Sensitive Neurorobotic Task Planning","date":"2024-06-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"xiao-wen-sun/ossa","path":"utils.py","file_url":"https://github.com/xiao-wen-sun/ossa/blob/HEAD/utils.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":"4dfe8592fa13dca7","mcp_get_code":{"code_sha256":"4dfe8592fa13dca7"}},{"arxiv_id":"openreview_Y3cUZ8fNnu","paper":null,"title":"arXiv:openreview_Y3cUZ8fNnu","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"chouliuzuo/IVQ","path":"vision_experiment/score/reconstruct.py","file_url":"https://github.com/chouliuzuo/IVQ/blob/HEAD/vision_experiment/score/reconstruct.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":"b52ca1186534e22a","mcp_get_code":{"code_sha256":"b52ca1186534e22a"}}]}