{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:HUD6CCV2V6NJI5FGF3WS3IWWBI","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":"72a814c95b255486fa3f570fec13080d4bdd7adc2a4b7976000b31a0eb68aa30","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-16T17:15:06Z","title_canon_sha256":"e282150a5959a87bbfbc2dfbdb59f921aac9972683426e99c84a7f41ef755723"},"schema_version":"1.0","source":{"id":"2507.12426","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.12426","created_at":"2026-07-05T11:39:14Z"},{"alias_kind":"arxiv_version","alias_value":"2507.12426v2","created_at":"2026-07-05T11:39:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.12426","created_at":"2026-07-05T11:39:14Z"},{"alias_kind":"pith_short_12","alias_value":"HUD6CCV2V6NJ","created_at":"2026-07-05T11:39:14Z"},{"alias_kind":"pith_short_16","alias_value":"HUD6CCV2V6NJI5FG","created_at":"2026-07-05T11:39:14Z"},{"alias_kind":"pith_short_8","alias_value":"HUD6CCV2","created_at":"2026-07-05T11:39:14Z"}],"graph_snapshots":[{"event_id":"sha256:2371b333c30bc67bab5e443a3652dad7555ea863f4e2a527fd645969a2005ff5","target":"graph","created_at":"2026-07-05T11:39:14Z","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/2507.12426/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The landscape of video recognition has evolved significantly, shifting from traditional Convolutional Neural Networks (CNNs) to Transformer-based architectures for improved accuracy. While 3D CNNs have been effective at capturing spatiotemporal dynamics, recent Transformer models leverage self-attention to model long-range spatial and temporal dependencies. Despite achieving state-of-the-art performance on major benchmarks, Transformers remain computationally expensive, particularly with dense video data. To address this, we propose a lightweight Video Focal Modulation Network, DVFL-Net, which","authors_text":"Abbas Khan, Arslan Munir, Hayat Ullah, Muhammad Ali Shafique","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-16T17:15:06Z","title":"DVFL-Net: A Lightweight Distilled Video Focal Modulation Network for Spatio-Temporal Action Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.12426","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":"sha256:32392b07f5a6e7f5409634b920454042fd3ebe342b529debb75f457fac56ba7d","target":"record","created_at":"2026-07-05T11:39:14Z","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":"72a814c95b255486fa3f570fec13080d4bdd7adc2a4b7976000b31a0eb68aa30","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-16T17:15:06Z","title_canon_sha256":"e282150a5959a87bbfbc2dfbdb59f921aac9972683426e99c84a7f41ef755723"},"schema_version":"1.0","source":{"id":"2507.12426","kind":"arxiv","version":2}},"canonical_sha256":"3d07e10abaaf9a9474a62eed2da2d60a3c4e738c9aef1e0260a8f8912622a3e8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3d07e10abaaf9a9474a62eed2da2d60a3c4e738c9aef1e0260a8f8912622a3e8","first_computed_at":"2026-07-05T11:39:14.896574Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:39:14.896574Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TmSFilLdmt6Wm26jpxw6l1Ba+5MNUrLI3WL4m1U+usPUVDrKNl6RI0KGQPpY5uCLjrG2bDNBrcJnFRvH0+olDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:39:14.897005Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.12426","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:32392b07f5a6e7f5409634b920454042fd3ebe342b529debb75f457fac56ba7d","sha256:2371b333c30bc67bab5e443a3652dad7555ea863f4e2a527fd645969a2005ff5"],"state_sha256":"af6cfdbda869a6d79eda5e7bb3a189b34c4a1f6cffa8ee501df55300f763fe55"}