{"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/build-resnet","entry":"build_resnet","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":7,"n_samples_ran":1,"n_samples_fingerprinted":0,"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":6},"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":"2605.31191","paper":"/paper/arxiv-2605-31191","title":"Student Capacity Moderates Knowledge Distillation Effectiveness: A Systematic Study Across ResNet Teacher-Student Pairs on CIFAR-10","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"umutonuryasar/kd-capacity-gap","path":"src/models/resnet.py","file_url":"https://github.com/umutonuryasar/kd-capacity-gap/blob/HEAD/src/models/resnet.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"0010520db0fd90b9","mcp_get_code":{"code_sha256":"0010520db0fd90b9"}},{"arxiv_id":"2306.12230","paper":"/paper/fantastic-weights-and-how-to-find-them-where-1","title":"Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training","date":"2023-06-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"TimDettmers/sparse_learning","path":"imagenet/tuned_resnet/resnet.py","file_url":"https://github.com/TimDettmers/sparse_learning/blob/HEAD/imagenet/tuned_resnet/resnet.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"51a6a5c2a049e900","mcp_get_code":{"code_sha256":"51a6a5c2a049e900"}},{"arxiv_id":"2306.12230","paper":"/paper/fantastic-weights-and-how-to-find-them-where-1","title":"Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training","date":"2023-06-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"alooow/fantastic_weights_paper","path":"ImageNet/resnet.py","file_url":"https://github.com/alooow/fantastic_weights_paper/blob/HEAD/ImageNet/resnet.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f069023ee573fe51","mcp_get_code":{"code_sha256":"f069023ee573fe51"}},{"arxiv_id":"2306.12230","paper":"/paper/fantastic-weights-and-how-to-find-them-where-1","title":"Fantastic Weights and How to Find Them: Where to Prune in Dynamic Sparse Training","date":"2023-06-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"alooow/fantastic_weights_paper","path":"models/imagenet_resnet.py","file_url":"https://github.com/alooow/fantastic_weights_paper/blob/HEAD/models/imagenet_resnet.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"61bbac980274b60d","mcp_get_code":{"code_sha256":"61bbac980274b60d"}},{"arxiv_id":"2208.01893","paper":"/paper/flow-annealed-importance-sampling-bootstrap","title":"Flow Annealed Importance Sampling Bootstrap","date":"2022-08-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"vislearn/trade","path":"trade/flow.py","file_url":"https://github.com/vislearn/trade/blob/HEAD/trade/flow.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":"cfb7a6f3f78317c8","mcp_get_code":{"code_sha256":"cfb7a6f3f78317c8"}},{"arxiv_id":"2205.00865","paper":"/paper/weatherbench-probability-a-benchmark-dataset","title":"WeatherBench Probability: A benchmark dataset for probabilistic medium-range weather forecasting along with deep learning baseline models","date":"2022-05-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sagar-garg/WeatherBench","path":"racecar_example.py","file_url":"https://github.com/sagar-garg/WeatherBench/blob/HEAD/racecar_example.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b5c03e96b1f7ebd1","mcp_get_code":{"code_sha256":"b5c03e96b1f7ebd1"}},{"arxiv_id":"2104.03133","paper":"/paper/image-composition-assessment-with-saliency","title":"Image Composition Assessment with Saliency-augmented Multi-pattern Pooling","date":"2021-04-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"bcmi/Image-Composition-Assessment-Dataset-CADB","path":"SAMPNet/samp_net.py","file_url":"https://github.com/bcmi/Image-Composition-Assessment-Dataset-CADB/blob/HEAD/SAMPNet/samp_net.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"c62f2b0d078c933f","mcp_get_code":{"code_sha256":"c62f2b0d078c933f"}}]}