{"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/cumsum","entry":"cumsum","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":5,"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":4,"n_places":6,"n_places_pointer_only":2,"by_status":{"ran_honours":1,"ran_violates":1,"ran_draft_wrong":0,"ran_fixture":1,"ran":1,"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":"2406.09031","paper":"/paper/a-comprehensive-graph-pooling-benchmark","title":"A Comprehensive Graph Pooling Benchmark: Effectiveness, Robustness and Generalizability","date":"2024-06-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"goose315/graph_pooling_benchmark","path":"Regression/models/baseline.py","file_url":"https://github.com/goose315/graph_pooling_benchmark/blob/HEAD/Regression/models/baseline.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"ddd7df1c4230b12d","mcp_get_code":{"code_sha256":"ddd7df1c4230b12d"}},{"arxiv_id":"2403.13795","paper":"/paper/pyvrp-a-high-performance-vrp-solver-package","title":"PyVRP: a high-performance VRP solver package","date":"2023-11-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Valdecy/pyVRP","path":"tests/test_evaluate_distance.py","file_url":"https://github.com/Valdecy/pyVRP/blob/HEAD/tests/test_evaluate_distance.py","status":"ran_violates","verification_level":2,"contract_check":"VIOLATES","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"84c0d42a93002d4e","mcp_get_code":{"code_sha256":"84c0d42a93002d4e"}},{"arxiv_id":"2311.07222","paper":"/paper/neural-general-circulation-models","title":"Neural General Circulation Models for Weather and Climate","date":"2023-11-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"google-research/dinosaur","path":"dinosaur/jax_numpy_utils.py","file_url":"https://github.com/google-research/dinosaur/blob/HEAD/dinosaur/jax_numpy_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":"ace0bd2565da2c28","mcp_get_code":{"code_sha256":"ace0bd2565da2c28"}},{"arxiv_id":"2307.01946","paper":"/paper/a-synthetic-electrocardiogram-ecg-image","title":"ECG-Image-Kit: A Synthetic Image Generation Toolbox to Facilitate Deep Learning-Based Electrocardiogram Digitization","date":"2023-07-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"alphanumericslab/ecg-image-kit","path":"codes/ecg-image-generator/HandwrittenText/generate.py","file_url":"https://github.com/alphanumericslab/ecg-image-kit/blob/HEAD/codes/ecg-image-generator/HandwrittenText/generate.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"9bafc68792a5453a","mcp_get_code":{"code_sha256":"9bafc68792a5453a"}},{"arxiv_id":"2304.06248","paper":"/paper/lasuie-unifying-information-extraction-with","title":"LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model","date":"2023-04-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"chocowu/lasuie","path":"engine/module.py","file_url":"https://github.com/chocowu/lasuie/blob/HEAD/engine/module.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"8e40a104d4067d24","mcp_get_code":{"code_sha256":"8e40a104d4067d24"}},{"arxiv_id":"1308.0850","paper":"/paper/generating-sequences-with-recurrent-neural","title":"Generating Sequences With Recurrent Neural Networks","date":"2013-08-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"grzego/handwriting-generation","path":"generate.py","file_url":"https://github.com/grzego/handwriting-generation/blob/HEAD/generate.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"9bafc68792a5453a","mcp_get_code":{"code_sha256":"9bafc68792a5453a"}}]}