{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:VP3BOYNOR2GAYTXJPKC7KOMO6S","short_pith_number":"pith:VP3BOYNO","canonical_record":{"source":{"id":"2410.02152","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-03T02:31:14Z","cross_cats_sorted":[],"title_canon_sha256":"8de7960e47884625013bc464e88fc2bdab36d569c6d41e387ec3ff9f7550b77b","abstract_canon_sha256":"612aa85f37417338731203e0dd191b45cce95e47a8c61c3fa57ae35be9da8b03"},"schema_version":"1.0"},"canonical_sha256":"abf61761ae8e8c0c4ee97a85f5398ef49cc4d5e31c487c1e3a374259d4ef7a56","source":{"kind":"arxiv","id":"2410.02152","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.02152","created_at":"2026-07-05T09:15:16Z"},{"alias_kind":"arxiv_version","alias_value":"2410.02152v1","created_at":"2026-07-05T09:15:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.02152","created_at":"2026-07-05T09:15:16Z"},{"alias_kind":"pith_short_12","alias_value":"VP3BOYNOR2GA","created_at":"2026-07-05T09:15:16Z"},{"alias_kind":"pith_short_16","alias_value":"VP3BOYNOR2GAYTXJ","created_at":"2026-07-05T09:15:16Z"},{"alias_kind":"pith_short_8","alias_value":"VP3BOYNO","created_at":"2026-07-05T09:15:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:VP3BOYNOR2GAYTXJPKC7KOMO6S","target":"record","payload":{"canonical_record":{"source":{"id":"2410.02152","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-03T02:31:14Z","cross_cats_sorted":[],"title_canon_sha256":"8de7960e47884625013bc464e88fc2bdab36d569c6d41e387ec3ff9f7550b77b","abstract_canon_sha256":"612aa85f37417338731203e0dd191b45cce95e47a8c61c3fa57ae35be9da8b03"},"schema_version":"1.0"},"canonical_sha256":"abf61761ae8e8c0c4ee97a85f5398ef49cc4d5e31c487c1e3a374259d4ef7a56","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:15:16.972889Z","signature_b64":"Q2Q31yIzpvaJVgOwRIe2lSWkXQ+MuWOmr+MZAD6ZnRwDepvoalaFwpOSuG3BA1I+MCZgXtCgmB1ohh+3gVHvCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"abf61761ae8e8c0c4ee97a85f5398ef49cc4d5e31c487c1e3a374259d4ef7a56","last_reissued_at":"2026-07-05T09:15:16.972368Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:15:16.972368Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.02152","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:15:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SzuGm9CiXygvL7o88RFWEkKq7j7QRprdGYtZ7C+GLh7+sjGIpwFzKLknhfotrGd7vZLrTXJ1jBUySpHrGT3aBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-20T11:38:58.347957Z"},"content_sha256":"9c93bc2a28f9284e53a1e3bd98167b93395c991a0f396c1d41dd499a73606462","schema_version":"1.0","event_id":"sha256:9c93bc2a28f9284e53a1e3bd98167b93395c991a0f396c1d41dd499a73606462"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:VP3BOYNOR2GAYTXJPKC7KOMO6S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An Evaluation of Large Pre-Trained Models for Gesture Recognition using Synthetic Videos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Arun Reddy, Celso M. de Melo, Corban Rivera, Ketul Shah, Rama Chellappa, William Paul","submitted_at":"2024-10-03T02:31:14Z","abstract_excerpt":"In this work, we explore the possibility of using synthetically generated data for video-based gesture recognition with large pre-trained models. We consider whether these models have sufficiently robust and expressive representation spaces to enable \"training-free\" classification. Specifically, we utilize various state-of-the-art video encoders to extract features for use in k-nearest neighbors classification, where the training data points are derived from synthetic videos only. We compare these results with another training-free approach -- zero-shot classification using text descriptions o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.02152","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2410.02152/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:15:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n5fCtBS0Cq58Vb146UMVZPgiO6s3S9uL6g/BHibdX+wn1QMxHMPSo7QdlqX/PV8A6vgdB5bcwYBBs6K9u6bVBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-20T11:38:58.348351Z"},"content_sha256":"3d117795cb314f6288a5cd41dbd41cfb4540f610bd60aa3d94a2876c06caf85d","schema_version":"1.0","event_id":"sha256:3d117795cb314f6288a5cd41dbd41cfb4540f610bd60aa3d94a2876c06caf85d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VP3BOYNOR2GAYTXJPKC7KOMO6S/bundle.json","state_url":"https://pith.science/pith/VP3BOYNOR2GAYTXJPKC7KOMO6S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VP3BOYNOR2GAYTXJPKC7KOMO6S/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-20T11:38:58Z","links":{"resolver":"https://pith.science/pith/VP3BOYNOR2GAYTXJPKC7KOMO6S","bundle":"https://pith.science/pith/VP3BOYNOR2GAYTXJPKC7KOMO6S/bundle.json","state":"https://pith.science/pith/VP3BOYNOR2GAYTXJPKC7KOMO6S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VP3BOYNOR2GAYTXJPKC7KOMO6S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:VP3BOYNOR2GAYTXJPKC7KOMO6S","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":"612aa85f37417338731203e0dd191b45cce95e47a8c61c3fa57ae35be9da8b03","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-03T02:31:14Z","title_canon_sha256":"8de7960e47884625013bc464e88fc2bdab36d569c6d41e387ec3ff9f7550b77b"},"schema_version":"1.0","source":{"id":"2410.02152","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.02152","created_at":"2026-07-05T09:15:16Z"},{"alias_kind":"arxiv_version","alias_value":"2410.02152v1","created_at":"2026-07-05T09:15:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.02152","created_at":"2026-07-05T09:15:16Z"},{"alias_kind":"pith_short_12","alias_value":"VP3BOYNOR2GA","created_at":"2026-07-05T09:15:16Z"},{"alias_kind":"pith_short_16","alias_value":"VP3BOYNOR2GAYTXJ","created_at":"2026-07-05T09:15:16Z"},{"alias_kind":"pith_short_8","alias_value":"VP3BOYNO","created_at":"2026-07-05T09:15:16Z"}],"graph_snapshots":[{"event_id":"sha256:3d117795cb314f6288a5cd41dbd41cfb4540f610bd60aa3d94a2876c06caf85d","target":"graph","created_at":"2026-07-05T09:15:16Z","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/2410.02152/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this work, we explore the possibility of using synthetically generated data for video-based gesture recognition with large pre-trained models. We consider whether these models have sufficiently robust and expressive representation spaces to enable \"training-free\" classification. Specifically, we utilize various state-of-the-art video encoders to extract features for use in k-nearest neighbors classification, where the training data points are derived from synthetic videos only. We compare these results with another training-free approach -- zero-shot classification using text descriptions o","authors_text":"Arun Reddy, Celso M. de Melo, Corban Rivera, Ketul Shah, Rama Chellappa, William Paul","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-03T02:31:14Z","title":"An Evaluation of Large Pre-Trained Models for Gesture Recognition using Synthetic Videos"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.02152","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":"sha256:9c93bc2a28f9284e53a1e3bd98167b93395c991a0f396c1d41dd499a73606462","target":"record","created_at":"2026-07-05T09:15:16Z","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":"612aa85f37417338731203e0dd191b45cce95e47a8c61c3fa57ae35be9da8b03","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-03T02:31:14Z","title_canon_sha256":"8de7960e47884625013bc464e88fc2bdab36d569c6d41e387ec3ff9f7550b77b"},"schema_version":"1.0","source":{"id":"2410.02152","kind":"arxiv","version":1}},"canonical_sha256":"abf61761ae8e8c0c4ee97a85f5398ef49cc4d5e31c487c1e3a374259d4ef7a56","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"abf61761ae8e8c0c4ee97a85f5398ef49cc4d5e31c487c1e3a374259d4ef7a56","first_computed_at":"2026-07-05T09:15:16.972368Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:15:16.972368Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Q2Q31yIzpvaJVgOwRIe2lSWkXQ+MuWOmr+MZAD6ZnRwDepvoalaFwpOSuG3BA1I+MCZgXtCgmB1ohh+3gVHvCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:15:16.972889Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.02152","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9c93bc2a28f9284e53a1e3bd98167b93395c991a0f396c1d41dd499a73606462","sha256:3d117795cb314f6288a5cd41dbd41cfb4540f610bd60aa3d94a2876c06caf85d"],"state_sha256":"2dc16a60fe378b83a2542eb64e3515e2a3163c3d5c9a52e704e1991f33ebac2e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N6u4aME3TsGYF1u3TirrRna45vedAbLms0od874Me3n5oS2/roFsj/SgX//8z/UJ/YoiwLyRjQTxH0jl0uTQBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-20T11:38:58.350907Z","bundle_sha256":"773f78eabf5ab2dc3a9177db977752c727c0db546a134611bfd05a127de86b37"}}