{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:XRD27ZI3DD5ORJZE35AWNJWYSO","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":"d7ed6575fcec28deb0f1504d2b4743bae5d1ef895b264ca424bda50ac0b36e24","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2014-06-24T14:16:56Z","title_canon_sha256":"b5f82e925cfd0bb4e0c5329f474e925ced6ad4ea003a1c9b76ce2934518d6c6e"},"schema_version":"1.0","source":{"id":"1406.6247","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1406.6247","created_at":"2026-05-18T02:49:03Z"},{"alias_kind":"arxiv_version","alias_value":"1406.6247v1","created_at":"2026-05-18T02:49:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1406.6247","created_at":"2026-05-18T02:49:03Z"},{"alias_kind":"pith_short_12","alias_value":"XRD27ZI3DD5O","created_at":"2026-05-18T12:28:57Z"},{"alias_kind":"pith_short_16","alias_value":"XRD27ZI3DD5ORJZE","created_at":"2026-05-18T12:28:57Z"},{"alias_kind":"pith_short_8","alias_value":"XRD27ZI3","created_at":"2026-05-18T12:28:57Z"}],"graph_snapshots":[{"event_id":"sha256:217ab19c8f36600b50ddeef9dc577a8ed89c9ac3670a9b1db03bc88486c0c208","target":"graph","created_at":"2026-05-18T02:49:03Z","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"},"paper":{"abstract_excerpt":"Applying convolutional neural networks to large images is computationally expensive because the amount of computation scales linearly with the number of image pixels. We present a novel recurrent neural network model that is capable of extracting information from an image or video by adaptively selecting a sequence of regions or locations and only processing the selected regions at high resolution. Like convolutional neural networks, the proposed model has a degree of translation invariance built-in, but the amount of computation it performs can be controlled independently of the input image s","authors_text":"Alex Graves, Koray Kavukcuoglu, Nicolas Heess, Volodymyr Mnih","cross_cats":["cs.CV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2014-06-24T14:16:56Z","title":"Recurrent Models of Visual Attention"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1406.6247","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":"sha256:8781e12d4861553b1e231544dd12ea9040ab91f3ef8819a959f66277db3967af","target":"record","created_at":"2026-05-18T02:49:03Z","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":"d7ed6575fcec28deb0f1504d2b4743bae5d1ef895b264ca424bda50ac0b36e24","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2014-06-24T14:16:56Z","title_canon_sha256":"b5f82e925cfd0bb4e0c5329f474e925ced6ad4ea003a1c9b76ce2934518d6c6e"},"schema_version":"1.0","source":{"id":"1406.6247","kind":"arxiv","version":1}},"canonical_sha256":"bc47afe51b18fae8a724df4166a6d8939ad542f34dd30b63d5d8fde3c3e9ff93","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bc47afe51b18fae8a724df4166a6d8939ad542f34dd30b63d5d8fde3c3e9ff93","first_computed_at":"2026-05-18T02:49:03.791346Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:49:03.791346Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"D084CnLqTpTWxrOW+Wl88ORksUSUxo62O9VrXkzmCdv8f1rJsN/ayuhqPOMIJZQyZTNCz5K7GOjARe7OKzxLAA==","signature_status":"signed_v1","signed_at":"2026-05-18T02:49:03.791792Z","signed_message":"canonical_sha256_bytes"},"source_id":"1406.6247","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8781e12d4861553b1e231544dd12ea9040ab91f3ef8819a959f66277db3967af","sha256:217ab19c8f36600b50ddeef9dc577a8ed89c9ac3670a9b1db03bc88486c0c208"],"state_sha256":"e2d4dfe7c7cb6f41e1b12ae81e3f8aa551685090eaef27b560192bae92391b6d"}