{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:WSFZW4ZN2UXHPA7TD2SD4LBMBL","short_pith_number":"pith:WSFZW4ZN","canonical_record":{"source":{"id":"1604.01729","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-04-06T19:01:28Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"bd0d4472e9dfd8afeca6dcfbf3b5cd4963b0bde3d5456207c229c3829a234f7b","abstract_canon_sha256":"1c07e16566750ee7ca107282fce27f65b5a905c3513898d5bc665c861951cf48"},"schema_version":"1.0"},"canonical_sha256":"b48b9b732dd52e7783f31ea43e2c2c0afbbe7a534e01a28ecca1f20541d7cd5d","source":{"kind":"arxiv","id":"1604.01729","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1604.01729","created_at":"2026-05-18T00:56:20Z"},{"alias_kind":"arxiv_version","alias_value":"1604.01729v2","created_at":"2026-05-18T00:56:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.01729","created_at":"2026-05-18T00:56:20Z"},{"alias_kind":"pith_short_12","alias_value":"WSFZW4ZN2UXH","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_16","alias_value":"WSFZW4ZN2UXHPA7T","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_8","alias_value":"WSFZW4ZN","created_at":"2026-05-18T12:30:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:WSFZW4ZN2UXHPA7TD2SD4LBMBL","target":"record","payload":{"canonical_record":{"source":{"id":"1604.01729","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-04-06T19:01:28Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"bd0d4472e9dfd8afeca6dcfbf3b5cd4963b0bde3d5456207c229c3829a234f7b","abstract_canon_sha256":"1c07e16566750ee7ca107282fce27f65b5a905c3513898d5bc665c861951cf48"},"schema_version":"1.0"},"canonical_sha256":"b48b9b732dd52e7783f31ea43e2c2c0afbbe7a534e01a28ecca1f20541d7cd5d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:56:20.776095Z","signature_b64":"Um/1fFokOdmVqIEyZYbDcVjkZYztD8AXC5J85wVz4/Oju/AZFu+VZPFZhKm9OpyFGBtf6PARJNXze8J3YSOjBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b48b9b732dd52e7783f31ea43e2c2c0afbbe7a534e01a28ecca1f20541d7cd5d","last_reissued_at":"2026-05-18T00:56:20.775410Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:56:20.775410Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1604.01729","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:56:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FpVmoy1IH9e7uNB3lTIiuUwDU2cEosbZeZ6Ad81I80+UsJpULTQtoRvlkfVp4jfbFhlcOZjIYyMVTZLdhLtMCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T15:26:47.285918Z"},"content_sha256":"764b1e225aa1c26b8b0c81b0901ea8eda3bb9afa96b73ad36ce35bfcb56606ea","schema_version":"1.0","event_id":"sha256:764b1e225aa1c26b8b0c81b0901ea8eda3bb9afa96b73ad36ce35bfcb56606ea"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:WSFZW4ZN2UXHPA7TD2SD4LBMBL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.CL","authors_text":"Kate Saenko, Lisa Anne Hendricks, Raymond Mooney, Subhashini Venugopalan","submitted_at":"2016-04-06T19:01:28Z","abstract_excerpt":"This paper investigates how linguistic knowledge mined from large text corpora can aid the generation of natural language descriptions of videos. Specifically, we integrate both a neural language model and distributional semantics trained on large text corpora into a recent LSTM-based architecture for video description. We evaluate our approach on a collection of Youtube videos as well as two large movie description datasets showing significant improvements in grammaticality while modestly improving descriptive quality."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.01729","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-18T00:56:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oC19tCqr58vsC59ZgE7H347I3Bs8kSu283EctpGAoIJt6D+vntco9Uy1vTPGumGornRP+2muER2wVBSTrpDXBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T15:26:47.286614Z"},"content_sha256":"0b5d7f6c6dddf032f01ec8775d9841fa1eaee54f604da891099d1b751cbb753e","schema_version":"1.0","event_id":"sha256:0b5d7f6c6dddf032f01ec8775d9841fa1eaee54f604da891099d1b751cbb753e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WSFZW4ZN2UXHPA7TD2SD4LBMBL/bundle.json","state_url":"https://pith.science/pith/WSFZW4ZN2UXHPA7TD2SD4LBMBL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WSFZW4ZN2UXHPA7TD2SD4LBMBL/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":"2026-05-25T15:26:47Z","links":{"resolver":"https://pith.science/pith/WSFZW4ZN2UXHPA7TD2SD4LBMBL","bundle":"https://pith.science/pith/WSFZW4ZN2UXHPA7TD2SD4LBMBL/bundle.json","state":"https://pith.science/pith/WSFZW4ZN2UXHPA7TD2SD4LBMBL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WSFZW4ZN2UXHPA7TD2SD4LBMBL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:WSFZW4ZN2UXHPA7TD2SD4LBMBL","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":"1c07e16566750ee7ca107282fce27f65b5a905c3513898d5bc665c861951cf48","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-04-06T19:01:28Z","title_canon_sha256":"bd0d4472e9dfd8afeca6dcfbf3b5cd4963b0bde3d5456207c229c3829a234f7b"},"schema_version":"1.0","source":{"id":"1604.01729","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1604.01729","created_at":"2026-05-18T00:56:20Z"},{"alias_kind":"arxiv_version","alias_value":"1604.01729v2","created_at":"2026-05-18T00:56:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.01729","created_at":"2026-05-18T00:56:20Z"},{"alias_kind":"pith_short_12","alias_value":"WSFZW4ZN2UXH","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_16","alias_value":"WSFZW4ZN2UXHPA7T","created_at":"2026-05-18T12:30:51Z"},{"alias_kind":"pith_short_8","alias_value":"WSFZW4ZN","created_at":"2026-05-18T12:30:51Z"}],"graph_snapshots":[{"event_id":"sha256:0b5d7f6c6dddf032f01ec8775d9841fa1eaee54f604da891099d1b751cbb753e","target":"graph","created_at":"2026-05-18T00:56:20Z","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":"This paper investigates how linguistic knowledge mined from large text corpora can aid the generation of natural language descriptions of videos. Specifically, we integrate both a neural language model and distributional semantics trained on large text corpora into a recent LSTM-based architecture for video description. We evaluate our approach on a collection of Youtube videos as well as two large movie description datasets showing significant improvements in grammaticality while modestly improving descriptive quality.","authors_text":"Kate Saenko, Lisa Anne Hendricks, Raymond Mooney, Subhashini Venugopalan","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-04-06T19:01:28Z","title":"Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.01729","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":"sha256:764b1e225aa1c26b8b0c81b0901ea8eda3bb9afa96b73ad36ce35bfcb56606ea","target":"record","created_at":"2026-05-18T00:56:20Z","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":"1c07e16566750ee7ca107282fce27f65b5a905c3513898d5bc665c861951cf48","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-04-06T19:01:28Z","title_canon_sha256":"bd0d4472e9dfd8afeca6dcfbf3b5cd4963b0bde3d5456207c229c3829a234f7b"},"schema_version":"1.0","source":{"id":"1604.01729","kind":"arxiv","version":2}},"canonical_sha256":"b48b9b732dd52e7783f31ea43e2c2c0afbbe7a534e01a28ecca1f20541d7cd5d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b48b9b732dd52e7783f31ea43e2c2c0afbbe7a534e01a28ecca1f20541d7cd5d","first_computed_at":"2026-05-18T00:56:20.775410Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:56:20.775410Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Um/1fFokOdmVqIEyZYbDcVjkZYztD8AXC5J85wVz4/Oju/AZFu+VZPFZhKm9OpyFGBtf6PARJNXze8J3YSOjBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:56:20.776095Z","signed_message":"canonical_sha256_bytes"},"source_id":"1604.01729","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:764b1e225aa1c26b8b0c81b0901ea8eda3bb9afa96b73ad36ce35bfcb56606ea","sha256:0b5d7f6c6dddf032f01ec8775d9841fa1eaee54f604da891099d1b751cbb753e"],"state_sha256":"d6208ccc75eb493a98f2b4f30eadfa03402619461966e5929010dd95a10c0aea"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pOwqpz+nsaHpJsyTUjdB5BkfUywa1IMceN0pvVyw/iM9gRJH0S8GDn6/vbG8RsqlXFNQZ9yjYBRFN72mOlIRCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T15:26:47.289411Z","bundle_sha256":"3e634cfa1c87461e175ad92213966da539eed5c08377dec333d100a7f5fc1827"}}