{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:X4ZHIT34OMCMBYSL5HVVR7VBVX","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":"f791f91c8e455f1c8ff05836dc5186e051fde9ca4ebe6ed56153169ae9b390b4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-28T10:32:03Z","title_canon_sha256":"ff25e55f1a37d5edc1dc879ed9a84c2499307253540706ee00f0aaef76725ed2"},"schema_version":"1.0","source":{"id":"1611.09053","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1611.09053","created_at":"2026-05-18T00:56:29Z"},{"alias_kind":"arxiv_version","alias_value":"1611.09053v1","created_at":"2026-05-18T00:56:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.09053","created_at":"2026-05-18T00:56:29Z"},{"alias_kind":"pith_short_12","alias_value":"X4ZHIT34OMCM","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_16","alias_value":"X4ZHIT34OMCMBYSL","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_8","alias_value":"X4ZHIT34","created_at":"2026-05-18T12:30:51Z"}],"graph_snapshots":[{"event_id":"sha256:d84f0d4086d10a2bba3b8342df66c9c57e14bc32486fdb5a0d1de8edc36a0627","target":"graph","created_at":"2026-05-18T00:56:29Z","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":"Despite the recent success of neural networks in image feature learning, a major problem in the video domain is the lack of sufficient labeled data for learning to model temporal information. In this paper, we propose an unsupervised temporal modeling method that learns from untrimmed videos. The speed of motion varies constantly, e.g., a man may run quickly or slowly. We therefore train a Multirate Visual Recurrent Model (MVRM) by encoding frames of a clip with different intervals. This learning process makes the learned model more capable of dealing with motion speed variance. Given a clip s","authors_text":"Linchao Zhu, Yi Yang, Zhongwen Xu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-28T10:32:03Z","title":"Bidirectional Multirate Reconstruction for Temporal Modeling in Videos"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.09053","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":"sha256:30b3e916be529b7e280dbc41e43b42db42697d60eaaa1592d24f6bf716aaba37","target":"record","created_at":"2026-05-18T00:56:29Z","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":"f791f91c8e455f1c8ff05836dc5186e051fde9ca4ebe6ed56153169ae9b390b4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-11-28T10:32:03Z","title_canon_sha256":"ff25e55f1a37d5edc1dc879ed9a84c2499307253540706ee00f0aaef76725ed2"},"schema_version":"1.0","source":{"id":"1611.09053","kind":"arxiv","version":1}},"canonical_sha256":"bf32744f7c7304c0e24be9eb58fea1ade0cabe63a502451ddf2f8774a95f6d39","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bf32744f7c7304c0e24be9eb58fea1ade0cabe63a502451ddf2f8774a95f6d39","first_computed_at":"2026-05-18T00:56:29.343893Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:56:29.343893Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CzRYXaao2jQqaz7N9W4GSWK4wyauZQPC6riQ/yH2TCvW0Ie7YgAfORTIdMSxYDY2WQgzRQ412UcsxaPHzFCLBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:56:29.344679Z","signed_message":"canonical_sha256_bytes"},"source_id":"1611.09053","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:30b3e916be529b7e280dbc41e43b42db42697d60eaaa1592d24f6bf716aaba37","sha256:d84f0d4086d10a2bba3b8342df66c9c57e14bc32486fdb5a0d1de8edc36a0627"],"state_sha256":"ef1fdb20c995bdb897fda9e4fec2528c3e8e9bae09e2fd0f1c49a69ff4484074"}