{"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/checkpoint-metric","entry":"checkpoint_metric","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":7,"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":2,"n_samples_ran":1,"n_samples_fingerprinted":1,"n_places":7,"n_places_pointer_only":0,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"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":"2402.04744","paper":"/paper/progressive-gradient-flow-for-robust-n-m","title":"Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers","date":"2024-02-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"abhibambhaniya/progressive_gradient_flow_nm_sparsity","path":"avg_checkpoints.py","file_url":"https://github.com/abhibambhaniya/progressive_gradient_flow_nm_sparsity/blob/HEAD/avg_checkpoints.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"33bca8cbc866bf64","mcp_get_code":{"code_sha256":"33bca8cbc866bf64"}},{"arxiv_id":"2401.17992","paper":"/paper/multilinear-operator-networks","title":"Multilinear Operator Networks","date":"2024-01-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Allencheng97/Multilinear_Operator_Networks","path":"avg_checkpoints.py","file_url":"https://github.com/Allencheng97/Multilinear_Operator_Networks/blob/HEAD/avg_checkpoints.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"33bca8cbc866bf64","mcp_get_code":{"code_sha256":"33bca8cbc866bf64"}},{"arxiv_id":"2305.17205","paper":"/paper/ghost-noise-for-regularizing-deep-neural","title":"Ghost Noise for Regularizing Deep Neural Networks","date":"2023-05-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"epfml/ghost-noise","path":"submodules/timm/avg_checkpoints.py","file_url":"https://github.com/epfml/ghost-noise/blob/HEAD/submodules/timm/avg_checkpoints.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"33bca8cbc866bf64","mcp_get_code":{"code_sha256":"33bca8cbc866bf64"}},{"arxiv_id":"2305.17190","paper":"/paper/multiplication-free-transformer-training-via-1","title":"Multiplication-Free Transformer Training via Piecewise Affine Operations","date":"2023-05-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"epfml/piecewise-affine-multiplication","path":"submodules/timm/avg_checkpoints.py","file_url":"https://github.com/epfml/piecewise-affine-multiplication/blob/HEAD/submodules/timm/avg_checkpoints.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"33bca8cbc866bf64","mcp_get_code":{"code_sha256":"33bca8cbc866bf64"}},{"arxiv_id":"2203.15207","paper":"/paper/generalizing-few-shot-nas-with-gradient-1","title":"Generalizing Few-Shot NAS with Gradient Matching","date":"2022-03-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"skhu101/GM-NAS","path":"Imagenet_train/avg_checkpoints.py","file_url":"https://github.com/skhu101/GM-NAS/blob/HEAD/Imagenet_train/avg_checkpoints.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"5954e4a7e67b4a0a","mcp_get_code":{"code_sha256":"5954e4a7e67b4a0a"}},{"arxiv_id":"2201.09792","paper":"/paper/patches-are-all-you-need-1","title":"Patches Are All You Need?","date":"2022-01-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tmp-iclr/convmixer","path":"pytorch-image-models/avg_checkpoints.py","file_url":"https://github.com/tmp-iclr/convmixer/blob/HEAD/pytorch-image-models/avg_checkpoints.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"33bca8cbc866bf64","mcp_get_code":{"code_sha256":"33bca8cbc866bf64"}},{"arxiv_id":"ijcai2023_0106","paper":null,"title":"arXiv:ijcai2023_0106","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"kkahatapitiya/SWAT","path":"avg_checkpoints.py","file_url":"https://github.com/kkahatapitiya/SWAT/blob/HEAD/avg_checkpoints.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"5954e4a7e67b4a0a","mcp_get_code":{"code_sha256":"5954e4a7e67b4a0a"}}]}