{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:U6SLNXK3HAKNVPBPUFECOIQAVO","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":"09f1322f86274c638541df9d57828f2cdff1daec662831249c5fc92f8369f72d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-08T22:25:34Z","title_canon_sha256":"9f5fb59235ae6e5ef174ea4fb82abe54d584ea7a1c49304e8911357e33259321"},"schema_version":"1.0","source":{"id":"2410.06405","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.06405","created_at":"2026-07-05T11:37:42Z"},{"alias_kind":"arxiv_version","alias_value":"2410.06405v2","created_at":"2026-07-05T11:37:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.06405","created_at":"2026-07-05T11:37:42Z"},{"alias_kind":"pith_short_12","alias_value":"U6SLNXK3HAKN","created_at":"2026-07-05T11:37:42Z"},{"alias_kind":"pith_short_16","alias_value":"U6SLNXK3HAKNVPBP","created_at":"2026-07-05T11:37:42Z"},{"alias_kind":"pith_short_8","alias_value":"U6SLNXK3","created_at":"2026-07-05T11:37:42Z"}],"graph_snapshots":[{"event_id":"sha256:49a06ee8704beea6df3eebb30d361fb0d69071ecc302cb5c29430c99af4ff53f","target":"graph","created_at":"2026-07-05T11:37:42Z","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/2410.06405/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The Abstraction and Reasoning Corpus (ARC) is a popular benchmark focused on visual reasoning in the evaluation of Artificial Intelligence systems. In its original framing, an ARC task requires solving a program synthesis problem over small 2D images using a few input-output training pairs. In this work, we adopt the recently popular data-driven approach to the ARC and ask whether a Vision Transformer (ViT) can learn the implicit mapping, from input image to output image, that underlies the task. We show that a ViT -- otherwise a state-of-the-art model for images -- fails dramatically on most ","authors_text":"Elias Boutros Khalil, Scott Sanner, Wenhao Li, Yudong Xu","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-08T22:25:34Z","title":"Tackling the Abstraction and Reasoning Corpus with Vision Transformers: the Importance of 2D Representation, Positions, and Objects"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.06405","kind":"arxiv","version":2},"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:b92d4fb37e8ee43c27ceb34b5ad36b8defea49d6cf5833ee261bbdc08f04c7ae","target":"record","created_at":"2026-07-05T11:37:42Z","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":"09f1322f86274c638541df9d57828f2cdff1daec662831249c5fc92f8369f72d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-08T22:25:34Z","title_canon_sha256":"9f5fb59235ae6e5ef174ea4fb82abe54d584ea7a1c49304e8911357e33259321"},"schema_version":"1.0","source":{"id":"2410.06405","kind":"arxiv","version":2}},"canonical_sha256":"a7a4b6dd5b3814dabc2fa148272200ab895bbb493e1445bbde10b7890069c6b7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a7a4b6dd5b3814dabc2fa148272200ab895bbb493e1445bbde10b7890069c6b7","first_computed_at":"2026-07-05T11:37:42.585753Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:37:42.585753Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"s/BUJ5OMOHpVwMW/rojVZZ9lBSEmVu4FhOGiKSYJrZrsR8xEFLDFivtIYxGEDVf0JZeXGfZzh4w3BgPkQm0hCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:37:42.586346Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.06405","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b92d4fb37e8ee43c27ceb34b5ad36b8defea49d6cf5833ee261bbdc08f04c7ae","sha256:49a06ee8704beea6df3eebb30d361fb0d69071ecc302cb5c29430c99af4ff53f"],"state_sha256":"9685fd0a5cdbfb8362e276a5bf0e8c9b9b05c81b878acdae4bce3b1a021fd609"}