{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:HEUFK7IGAXA63SNS7HEX3O4LZN","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":"7fb229ba6f84adac9db9b9925dfafbac2e467c15d1edab9a0f3717005916780f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-01-24T03:28:37Z","title_canon_sha256":"e792f6bccfc410722f45f64bedcacf1ed903fb7d7c9f1dc1b1c6cbb8a58314ae"},"schema_version":"1.0","source":{"id":"2501.14210","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.14210","created_at":"2026-07-05T10:04:47Z"},{"alias_kind":"arxiv_version","alias_value":"2501.14210v1","created_at":"2026-07-05T10:04:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.14210","created_at":"2026-07-05T10:04:47Z"},{"alias_kind":"pith_short_12","alias_value":"HEUFK7IGAXA6","created_at":"2026-07-05T10:04:47Z"},{"alias_kind":"pith_short_16","alias_value":"HEUFK7IGAXA63SNS","created_at":"2026-07-05T10:04:47Z"},{"alias_kind":"pith_short_8","alias_value":"HEUFK7IG","created_at":"2026-07-05T10:04:47Z"}],"graph_snapshots":[{"event_id":"sha256:dacaec8ac78ef2634f02b4393f1fb58ffb944982d3be5ffdd4f7d565cbb53cb4","target":"graph","created_at":"2026-07-05T10:04:47Z","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/2501.14210/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The task of predicting time and location from images is challenging and requires complex human-like puzzle-solving ability over different clues. In this work, we formalize this ability into core skills and implement them using different modules in an expert pipeline called PuzzleGPT. PuzzleGPT consists of a perceiver to identify visual clues, a reasoner to deduce prediction candidates, a combiner to combinatorially combine information from different clues, a web retriever to get external knowledge if the task can't be solved locally, and a noise filter for robustness. This results in a zero-sh","authors_text":"Hammad Ayyubi, Junzhang Liu, Shih-Fu Chang, Xuande Feng, Xudong Lin, Zhecan Wang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-01-24T03:28:37Z","title":"PuzzleGPT: Emulating Human Puzzle-Solving Ability for Time and Location Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.14210","kind":"arxiv","version":1},"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":"sha256:0417d740894f9e31c83bf198b60f0ec716bd304aaa2f1eef9b50835545b24df4","target":"record","created_at":"2026-07-05T10:04:47Z","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":"7fb229ba6f84adac9db9b9925dfafbac2e467c15d1edab9a0f3717005916780f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-01-24T03:28:37Z","title_canon_sha256":"e792f6bccfc410722f45f64bedcacf1ed903fb7d7c9f1dc1b1c6cbb8a58314ae"},"schema_version":"1.0","source":{"id":"2501.14210","kind":"arxiv","version":1}},"canonical_sha256":"3928557d0605c1edc9b2f9c97dbb8bcb6b4dc6a7e2968bd1066ee22775addcc9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3928557d0605c1edc9b2f9c97dbb8bcb6b4dc6a7e2968bd1066ee22775addcc9","first_computed_at":"2026-07-05T10:04:47.264845Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:04:47.264845Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hl9wx6QH3N21SMpPViYmOdTNhbeFl8GRdApe6JumOHOZCCIwoV6mkf/NrvflGXkYTquRhOQtIuf2OLrxpemqAA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:04:47.265345Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.14210","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0417d740894f9e31c83bf198b60f0ec716bd304aaa2f1eef9b50835545b24df4","sha256:dacaec8ac78ef2634f02b4393f1fb58ffb944982d3be5ffdd4f7d565cbb53cb4"],"state_sha256":"e1eba75e05e511ce92d7a5401657d9a5638d848bdc9843021ebb933c7ac1f7f7"}