{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:4OKG6S3PRUJ4XXCCT7M4NPUCUS","short_pith_number":"pith:4OKG6S3P","canonical_record":{"source":{"id":"1806.00257","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MM","submitted_at":"2018-06-01T09:44:56Z","cross_cats_sorted":[],"title_canon_sha256":"63df30bb613f53d3ce83612f6914082ec733ffa5d466c08085b488add0f160f7","abstract_canon_sha256":"d968ce1333d3372461e15aab4ba913bd337a552c93aa73a63d40bcc83e72bd42"},"schema_version":"1.0"},"canonical_sha256":"e3946f4b6f8d13cbdc429fd9c6be82a4b2675e64a06b98cda4d5a1adaa8d8cbc","source":{"kind":"arxiv","id":"1806.00257","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.00257","created_at":"2026-05-18T00:14:24Z"},{"alias_kind":"arxiv_version","alias_value":"1806.00257v1","created_at":"2026-05-18T00:14:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.00257","created_at":"2026-05-18T00:14:24Z"},{"alias_kind":"pith_short_12","alias_value":"4OKG6S3PRUJ4","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_16","alias_value":"4OKG6S3PRUJ4XXCC","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_8","alias_value":"4OKG6S3P","created_at":"2026-05-18T12:32:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:4OKG6S3PRUJ4XXCCT7M4NPUCUS","target":"record","payload":{"canonical_record":{"source":{"id":"1806.00257","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MM","submitted_at":"2018-06-01T09:44:56Z","cross_cats_sorted":[],"title_canon_sha256":"63df30bb613f53d3ce83612f6914082ec733ffa5d466c08085b488add0f160f7","abstract_canon_sha256":"d968ce1333d3372461e15aab4ba913bd337a552c93aa73a63d40bcc83e72bd42"},"schema_version":"1.0"},"canonical_sha256":"e3946f4b6f8d13cbdc429fd9c6be82a4b2675e64a06b98cda4d5a1adaa8d8cbc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:24.242589Z","signature_b64":"xO4TVph6DSiYBYNy0cVEyQRA7KWNb6+F4rL9ZkwGmK6JpNpEkCaLQHl++Mx26wgRJNEk4Hpqq6ql6QVvIXIACQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e3946f4b6f8d13cbdc429fd9c6be82a4b2675e64a06b98cda4d5a1adaa8d8cbc","last_reissued_at":"2026-05-18T00:14:24.241819Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:24.241819Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.00257","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":"2026-05-18T00:14:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gi+Ng/tE0u9LT0PdD/rMsuKHRr10ZcgG92cWZn50yvuGFoh/Gx9L6sIT7cOA9UJGXpwlOTTTLk0C2q9wg8DtAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T20:07:54.980297Z"},"content_sha256":"6019a3d76a66d508df9b5aa18a8e061eba6f9f1d3a69f87e03ccf55154488d56","schema_version":"1.0","event_id":"sha256:6019a3d76a66d508df9b5aa18a8e061eba6f9f1d3a69f87e03ccf55154488d56"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:4OKG6S3PRUJ4XXCCT7M4NPUCUS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Synchronous Prediction of Arousal and Valence Using LSTM Network for Affective Video Content Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.MM","authors_text":"Jiulong Zhang, Ligang Zhang","submitted_at":"2018-06-01T09:44:56Z","abstract_excerpt":"The affect embedded in video data conveys high-level semantic information about the content and has direct impact on the understanding and perception of reviewers, as well as their emotional responses. Affective Video Content Analysis (AVCA) attempts to generate a direct mapping between video content and the corresponding affective states such as arousal and valence dimensions. Most existing studies establish the mapping for each dimension separately using knowledge-based rules or traditional classifiers such as Support Vector Machine (SVM). The inherent correlations between affective dimensio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.00257","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":""},"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":"2026-05-18T00:14:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MdYgbPzmE55g5XP3JVWXmx9BpwrnvFZSFEuDcLBOOEFgWEEE0l7lO0cMsKugKnCYIoYktk9BcZJ5EzykkwaIAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T20:07:54.980923Z"},"content_sha256":"9cc276d0a1c659d15839a880cd50d1ed343b3193dcc9533430e6670ca9c216e7","schema_version":"1.0","event_id":"sha256:9cc276d0a1c659d15839a880cd50d1ed343b3193dcc9533430e6670ca9c216e7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4OKG6S3PRUJ4XXCCT7M4NPUCUS/bundle.json","state_url":"https://pith.science/pith/4OKG6S3PRUJ4XXCCT7M4NPUCUS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4OKG6S3PRUJ4XXCCT7M4NPUCUS/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":"2026-05-31T20:07:54Z","links":{"resolver":"https://pith.science/pith/4OKG6S3PRUJ4XXCCT7M4NPUCUS","bundle":"https://pith.science/pith/4OKG6S3PRUJ4XXCCT7M4NPUCUS/bundle.json","state":"https://pith.science/pith/4OKG6S3PRUJ4XXCCT7M4NPUCUS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4OKG6S3PRUJ4XXCCT7M4NPUCUS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:4OKG6S3PRUJ4XXCCT7M4NPUCUS","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":"d968ce1333d3372461e15aab4ba913bd337a552c93aa73a63d40bcc83e72bd42","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MM","submitted_at":"2018-06-01T09:44:56Z","title_canon_sha256":"63df30bb613f53d3ce83612f6914082ec733ffa5d466c08085b488add0f160f7"},"schema_version":"1.0","source":{"id":"1806.00257","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.00257","created_at":"2026-05-18T00:14:24Z"},{"alias_kind":"arxiv_version","alias_value":"1806.00257v1","created_at":"2026-05-18T00:14:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.00257","created_at":"2026-05-18T00:14:24Z"},{"alias_kind":"pith_short_12","alias_value":"4OKG6S3PRUJ4","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_16","alias_value":"4OKG6S3PRUJ4XXCC","created_at":"2026-05-18T12:32:05Z"},{"alias_kind":"pith_short_8","alias_value":"4OKG6S3P","created_at":"2026-05-18T12:32:05Z"}],"graph_snapshots":[{"event_id":"sha256:9cc276d0a1c659d15839a880cd50d1ed343b3193dcc9533430e6670ca9c216e7","target":"graph","created_at":"2026-05-18T00:14:24Z","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":"The affect embedded in video data conveys high-level semantic information about the content and has direct impact on the understanding and perception of reviewers, as well as their emotional responses. Affective Video Content Analysis (AVCA) attempts to generate a direct mapping between video content and the corresponding affective states such as arousal and valence dimensions. Most existing studies establish the mapping for each dimension separately using knowledge-based rules or traditional classifiers such as Support Vector Machine (SVM). The inherent correlations between affective dimensio","authors_text":"Jiulong Zhang, Ligang Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MM","submitted_at":"2018-06-01T09:44:56Z","title":"Synchronous Prediction of Arousal and Valence Using LSTM Network for Affective Video Content Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.00257","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":"sha256:6019a3d76a66d508df9b5aa18a8e061eba6f9f1d3a69f87e03ccf55154488d56","target":"record","created_at":"2026-05-18T00:14:24Z","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":"d968ce1333d3372461e15aab4ba913bd337a552c93aa73a63d40bcc83e72bd42","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MM","submitted_at":"2018-06-01T09:44:56Z","title_canon_sha256":"63df30bb613f53d3ce83612f6914082ec733ffa5d466c08085b488add0f160f7"},"schema_version":"1.0","source":{"id":"1806.00257","kind":"arxiv","version":1}},"canonical_sha256":"e3946f4b6f8d13cbdc429fd9c6be82a4b2675e64a06b98cda4d5a1adaa8d8cbc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e3946f4b6f8d13cbdc429fd9c6be82a4b2675e64a06b98cda4d5a1adaa8d8cbc","first_computed_at":"2026-05-18T00:14:24.241819Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:24.241819Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xO4TVph6DSiYBYNy0cVEyQRA7KWNb6+F4rL9ZkwGmK6JpNpEkCaLQHl++Mx26wgRJNEk4Hpqq6ql6QVvIXIACQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:24.242589Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.00257","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6019a3d76a66d508df9b5aa18a8e061eba6f9f1d3a69f87e03ccf55154488d56","sha256:9cc276d0a1c659d15839a880cd50d1ed343b3193dcc9533430e6670ca9c216e7"],"state_sha256":"66df23495a4a38cd9591e3adb98bc8afbd3d6308b10596f78a395d56bc3ad70f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"23vzYJOIz5gOIZHMPyj5RENfhZauJz1hg+Qt2sRy+nJbmwoKnCw7yCTC4YthhPPU2uwW0OTQpy9eHWvUshh5CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T20:07:54.984525Z","bundle_sha256":"f473275cdb5d019540180db41edfdec805b56664fb8347bf2e9a2e2f6fb8d8fa"}}