{"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-dataloaders","entry":"build_dataloaders","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":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":2,"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":"2608.20134","paper":"/paper/arxiv-2608-20134","title":"Feature Evolution and Migration during Vision Transformer Training *","date":null,"month_inferred_from_arxiv_id":"2026-08","title_source":"syntology","repo":"joonasrooben/VIT-Feature-Evolution-and-Migration","path":"generate_acts_vit_fun_tiny.py","file_url":"https://github.com/joonasrooben/VIT-Feature-Evolution-and-Migration/blob/HEAD/generate_acts_vit_fun_tiny.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"cf747bedb0096952","mcp_get_code":{"code_sha256":"cf747bedb0096952"}},{"arxiv_id":"2602.18406","paper":"/paper/arxiv-2602-18406","title":"GRaM workshop at ICLR 2026 Tiny Paper Track LATENT EQUIVARIANT OPERATORS FOR ROBUST OBJECT RECOGNITION: PROMISES AND CHALLENGES","date":"2026-02-20","month_inferred_from_arxiv_id":null,"title_source":"syntology","repo":"BRAIN-Aalto/equivariant_operator","path":"mnist_train_cls.py","file_url":"https://github.com/BRAIN-Aalto/equivariant_operator/blob/HEAD/mnist_train_cls.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"1115223db7dc1b2b","mcp_get_code":{"code_sha256":"1115223db7dc1b2b"}},{"arxiv_id":"2307.08243","paper":"/paper/uncertainty-aware-state-space-transformer-for","title":"Uncertainty-aware State Space Transformer for Egocentric 3D Hand Trajectory Forecasting","date":"2023-07-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"oppo-us-research/USST","path":"src/EgoPAT3DLoader.py","file_url":"https://github.com/oppo-us-research/USST/blob/HEAD/src/EgoPAT3DLoader.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":"92f4580f0daea9e6","mcp_get_code":{"code_sha256":"92f4580f0daea9e6"}},{"arxiv_id":"2212.10554","paper":"/paper/a-length-extrapolatable-transformer","title":"A Length-Extrapolatable Transformer","date":"2022-12-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"conceptofmind/palm","path":"palm/build_dataloaders.py","file_url":"https://github.com/conceptofmind/palm/blob/HEAD/palm/build_dataloaders.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a45309570f26c6bf","mcp_get_code":{"code_sha256":"a45309570f26c6bf"}},{"arxiv_id":"2205.11718","paper":"/paper/semi-parametric-deep-neural-networks-in","title":"Semi-Parametric Inducing Point Networks and Neural Processes","date":"2022-05-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"richrast/spin","path":"baselines/models/dkl_run.py","file_url":"https://github.com/richrast/spin/blob/HEAD/baselines/models/dkl_run.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":"b7b4bab81728304c","mcp_get_code":{"code_sha256":"b7b4bab81728304c"}},{"arxiv_id":"2205.11718","paper":"/paper/semi-parametric-deep-neural-networks-in","title":"Semi-Parametric Inducing Point Networks and Neural Processes","date":"2022-05-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"richrast/spin","path":"baselines/models/mc_dropout_run.py","file_url":"https://github.com/richrast/spin/blob/HEAD/baselines/models/mc_dropout_run.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":"bdaa232146fb8a71","mcp_get_code":{"code_sha256":"bdaa232146fb8a71"}},{"arxiv_id":"1710.09829","paper":"/paper/dynamic-routing-between-capsules","title":"Dynamic Routing Between Capsules","date":"2017-10-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ethanleet/CapsNet","path":"data_loaders.py","file_url":"https://github.com/ethanleet/CapsNet/blob/HEAD/data_loaders.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ef26365c2b293ba7","mcp_get_code":{"code_sha256":"ef26365c2b293ba7"}}]}