{"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/resnet-18","entry":"resnet_18","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":5,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":4,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"unverified":4},"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":"2509.21387","paper":"/paper/arxiv-2509-21387","title":"Do Sparse Subnetworks Exhibit Cognitively Aligned Attention? Effects of Pruning on Saliency Map Fidelity, Sparsity, and Concept Coherence","date":null,"month_inferred_from_arxiv_id":"2025-09","title_source":"syntology","repo":"sanishsuwal7/Neurips-CogInterp","path":"code/resnet/resnet_18.py","file_url":"https://github.com/sanishsuwal7/Neurips-CogInterp/blob/HEAD/code/resnet/resnet_18.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"7b2e0837a82d2a45","mcp_get_code":{"code_sha256":"7b2e0837a82d2a45"}},{"arxiv_id":"2405.19654","paper":"/paper/unlocking-the-power-of-spatial-and-temporal","title":"Unlocking the Power of Spatial and Temporal Information in Medical Multimodal Pre-training","date":"2024-05-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"svt-yang/medst","path":"medst/models/backbones/cnn_backbones.py","file_url":"https://github.com/svt-yang/medst/blob/HEAD/medst/models/backbones/cnn_backbones.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"4fe94741be065e60","mcp_get_code":{"code_sha256":"4fe94741be065e60"}},{"arxiv_id":"2312.10251","paper":"/paper/advancing-surgical-vqa-with-scene-graph","title":"Advancing Surgical VQA with Scene Graph Knowledge","date":"2023-12-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"camma-public/ssg-qa","path":"models/resnets.py","file_url":"https://github.com/camma-public/ssg-qa/blob/HEAD/models/resnets.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"9ac87a0b75aa2d0d","mcp_get_code":{"code_sha256":"9ac87a0b75aa2d0d"}},{"arxiv_id":"2312.01522","paper":"/paper/g2d-from-global-to-dense-radiography","title":"G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training","date":"2023-12-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"cheliu-computation/g2d-neurips24","path":"PRETRAIN/models/cnn_encoder.py","file_url":"https://github.com/cheliu-computation/g2d-neurips24/blob/HEAD/PRETRAIN/models/cnn_encoder.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"04b63bf6654c37bf","mcp_get_code":{"code_sha256":"04b63bf6654c37bf"}},{"arxiv_id":"1910.08525","paper":"/paper/scheduling-the-learning-rate-via-1","title":"MARTHE: Scheduling the Learning Rate Via Online Hypergradients","date":"2019-10-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"awslabs/adatune","path":"adatune/network.py","file_url":"https://github.com/awslabs/adatune/blob/HEAD/adatune/network.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":"6edde11b8ad65d09","mcp_get_code":{"code_sha256":"6edde11b8ad65d09"}}]}