{"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/split-indices","entry":"split_indices","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":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":5,"n_samples_ran":4,"n_samples_fingerprinted":1,"n_places":5,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":3,"unverified":1},"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":"2607.14249","paper":"/paper/arxiv-2607-14249","title":"MIDiff: Tackling Sparsity and Imbalance in Mobile Usage Generation via Multivariate-Imaging Diffusion","date":null,"month_inferred_from_arxiv_id":"2026-07","title_source":"syntology","repo":"YilaiLiu-HKU/MIDiff","path":"exp/run_downstream_cross_variable.py","file_url":"https://github.com/YilaiLiu-HKU/MIDiff/blob/HEAD/exp/run_downstream_cross_variable.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"17a265daf892dd60","mcp_get_code":{"code_sha256":"17a265daf892dd60"}},{"arxiv_id":"2606.20993","paper":"/paper/arxiv-2606-20993","title":"Phonemes to the Rescue: Multilingual Tokenization Based on International Phonetic Alphabet","date":null,"month_inferred_from_arxiv_id":"2026-06","title_source":"syntology","repo":"Mikki99/ipa-tokenization","path":"src/ipa_tok/gpt2/cache.py","file_url":"https://github.com/Mikki99/ipa-tokenization/blob/HEAD/src/ipa_tok/gpt2/cache.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"e7b86614beeddd58","mcp_get_code":{"code_sha256":"e7b86614beeddd58"}},{"arxiv_id":"2606.18850","paper":"/paper/arxiv-2606-18850","title":"ScholarSum: Student-Teacher Abstractive Summarization via Knowledge Graph Reasoning and Reflective Refinement","date":null,"month_inferred_from_arxiv_id":"2026-06","title_source":"syntology","repo":"Xiaoyu-Tao/ScholarSum","path":"src/papersum/pipeline.py","file_url":"https://github.com/Xiaoyu-Tao/ScholarSum/blob/HEAD/src/papersum/pipeline.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"95f3f0f1b54ce2be","mcp_get_code":{"code_sha256":"95f3f0f1b54ce2be"}},{"arxiv_id":"2602.00333","paper":"/paper/arxiv-2602-00333","title":"Efficient and accurate steering of Large Language Models through attention-guided feature learning","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"pdavar/attention_guided_steering","path":"control_toolkits.py","file_url":"https://github.com/pdavar/attention_guided_steering/blob/HEAD/control_toolkits.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"a42bbfb14a05ac2f","mcp_get_code":{"code_sha256":"a42bbfb14a05ac2f"}},{"arxiv_id":"2406.14794","paper":"/paper/imageflownet-forecasting-multiscale","title":"ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images","date":"2024-06-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ChenLiu-1996/ImageFlowNet","path":"src/data_utils/split.py","file_url":"https://github.com/ChenLiu-1996/ImageFlowNet/blob/HEAD/src/data_utils/split.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"71614413f7121e9d","mcp_get_code":{"code_sha256":"71614413f7121e9d"}}]}