{"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/binaryconv3x3","entry":"binaryconv3x3","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":2,"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":2,"n_samples_fingerprinted":0,"n_places":7,"n_places_pointer_only":3,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":2,"ran_fixture":0,"ran":0,"unverified":5},"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":"2305.10299","paper":"/paper/binarized-spectral-compressive-imaging-1","title":"Binarized Spectral Compressive Imaging","date":"2023-05-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"caiyuanhao1998/BiSCI","path":"real/test_code/architecture/BirealNet.py","file_url":"https://github.com/caiyuanhao1998/BiSCI/blob/HEAD/real/test_code/architecture/BirealNet.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"31e65d8d2a126bf7","mcp_get_code":{"code_sha256":"31e65d8d2a126bf7"}},{"arxiv_id":"2305.10299","paper":"/paper/binarized-spectral-compressive-imaging-1","title":"Binarized Spectral Compressive Imaging","date":"2023-05-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"caiyuanhao1998/BiSCI","path":"real/test_code/architecture/IRNet.py","file_url":"https://github.com/caiyuanhao1998/BiSCI/blob/HEAD/real/test_code/architecture/IRNet.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"73a38f446f78bba0","mcp_get_code":{"code_sha256":"73a38f446f78bba0"}},{"arxiv_id":"2305.10299","paper":"/paper/binarized-spectral-compressive-imaging-1","title":"Binarized Spectral Compressive Imaging","date":"2023-05-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"caiyuanhao1998/BiSCI","path":"real/test_code/architecture/ReActNet.py","file_url":"https://github.com/caiyuanhao1998/BiSCI/blob/HEAD/real/test_code/architecture/ReActNet.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"0e5a72e209254e33","mcp_get_code":{"code_sha256":"0e5a72e209254e33"}},{"arxiv_id":"2209.01404","paper":"/paper/towards-accurate-binary-neural-networks-via","title":"Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies","date":"2022-09-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Sense-GVT/BCDNet","path":"prototype/model/a_3.py","file_url":"https://github.com/Sense-GVT/BCDNet/blob/HEAD/prototype/model/a_3.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c8fd8f1b353d36a3","mcp_get_code":{"code_sha256":"c8fd8f1b353d36a3"}},{"arxiv_id":"2201.07703","paper":"/paper/q-vit-fully-differentiable-quantization-for","title":"Q-ViT: Fully Differentiable Quantization for Vision Transformer","date":"2022-01-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhexinli/Q-ViT-DeiT","path":"quantization/binary_layer.py","file_url":"https://github.com/zhexinli/Q-ViT-DeiT/blob/HEAD/quantization/binary_layer.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":false,"code_sha256_prefix":"80f2879bb6f51376","mcp_get_code":{"code_sha256":"80f2879bb6f51376"}},{"arxiv_id":"2104.08215","paper":"/paper/bnn-bn-training-binary-neural-networks","title":"\"BNN - BN = ?\": Training Binary Neural Networks without Batch Normalization","date":"2021-04-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"VITA-Group/BNN_NoBN","path":"models/Qa_reactnet_18_bf.py","file_url":"https://github.com/VITA-Group/BNN_NoBN/blob/HEAD/models/Qa_reactnet_18_bf.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"7fbee15b94a45d5d","mcp_get_code":{"code_sha256":"7fbee15b94a45d5d"}},{"arxiv_id":"2102.08946","paper":"/paper/s2-bnn-bridging-the-gap-between-self","title":"S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration","date":"2021-02-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"szq0214/S2-BNN","path":"Contrastive+Distillation/step2/ReActNet.py","file_url":"https://github.com/szq0214/S2-BNN/blob/HEAD/Contrastive%2BDistillation/step2/ReActNet.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"a9aa7207ec783915","mcp_get_code":{"code_sha256":"a9aa7207ec783915"}}]}