{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:53DNKZX2JGXTFW4ZANE356GIB7","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"29a0304033a3fbeae04ff57813326a424ab867b1d90c99639c4dd4b53911530f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-03-23T17:56:06Z","title_canon_sha256":"c71a6742ca0ac82e863349c22e5aa72b77f3544c0173201683c9ab1334562f01"},"schema_version":"1.0","source":{"id":"2103.12731","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2103.12731","created_at":"2026-07-05T02:46:45Z"},{"alias_kind":"arxiv_version","alias_value":"2103.12731v3","created_at":"2026-07-05T02:46:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.12731","created_at":"2026-07-05T02:46:45Z"},{"alias_kind":"pith_short_12","alias_value":"53DNKZX2JGXT","created_at":"2026-07-05T02:46:45Z"},{"alias_kind":"pith_short_16","alias_value":"53DNKZX2JGXTFW4Z","created_at":"2026-07-05T02:46:45Z"},{"alias_kind":"pith_short_8","alias_value":"53DNKZX2","created_at":"2026-07-05T02:46:45Z"}],"graph_snapshots":[{"event_id":"sha256:519da5ad9f13c08ec02a82015ebb5d65f82240a1c72aacbb91e798da514dde57","target":"graph","created_at":"2026-07-05T02:46:45Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2103.12731/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Self-attention has the promise of improving computer vision systems due to parameter-independent scaling of receptive fields and content-dependent interactions, in contrast to parameter-dependent scaling and content-independent interactions of convolutions. Self-attention models have recently been shown to have encouraging improvements on accuracy-parameter trade-offs compared to baseline convolutional models such as ResNet-50. In this work, we aim to develop self-attention models that can outperform not just the canonical baseline models, but even the high-performing convolutional models. We ","authors_text":"Aravind Srinivas, Ashish Vaswani, Blake Hechtman, Jonathon Shlens, Niki Parmar, Prajit Ramachandran","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-03-23T17:56:06Z","title":"Scaling Local Self-Attention for Parameter Efficient Visual Backbones"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.12731","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:b363233570fde864b482c177ecd6c5993df5387414b89095eb8bd4d82929b4ca","target":"record","created_at":"2026-07-05T02:46:45Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"29a0304033a3fbeae04ff57813326a424ab867b1d90c99639c4dd4b53911530f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-03-23T17:56:06Z","title_canon_sha256":"c71a6742ca0ac82e863349c22e5aa72b77f3544c0173201683c9ab1334562f01"},"schema_version":"1.0","source":{"id":"2103.12731","kind":"arxiv","version":3}},"canonical_sha256":"eec6d566fa49af32db990349bef8c80fe992714d651052f7215ca3a129fbbe0e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eec6d566fa49af32db990349bef8c80fe992714d651052f7215ca3a129fbbe0e","first_computed_at":"2026-07-05T02:46:45.102635Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:46:45.102635Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"juR72YoypH1F6RE0TJ7jens8gm9N4ZsXcmOKdxOSnbgw2lD3vF49kahZcPOR1fl0YUPnJ55iCsT08rY/YafiAA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:46:45.103048Z","signed_message":"canonical_sha256_bytes"},"source_id":"2103.12731","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b363233570fde864b482c177ecd6c5993df5387414b89095eb8bd4d82929b4ca","sha256:519da5ad9f13c08ec02a82015ebb5d65f82240a1c72aacbb91e798da514dde57"],"state_sha256":"5dcff904c4c8b2ca8dfb2419c5b43891b8830c884349d118853d7404d068cf1d"}