{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:IP4OTPOMFFSEI34HX7UFOP2OIR","short_pith_number":"pith:IP4OTPOM","schema_version":"1.0","canonical_sha256":"43f8e9bdcc2964446f87bfe8573f4e4471898f7707710850366bcc10091bea89","source":{"kind":"arxiv","id":"2103.02362","version":3},"attestation_state":"computed","paper":{"title":"Video Sentiment Analysis with Bimodal Information-augmented Multi-Head Attention","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Chuanshuai Ma, Huiran Zhang, Junjie Peng, Ting Wu, Wenqiang Zhang, Yansong Huang","submitted_at":"2021-03-03T12:30:11Z","abstract_excerpt":"Humans express feelings or emotions via different channels. Take language as an example, it entails different sentiments under different visual-acoustic contexts. To precisely understand human intentions as well as reduce the misunderstandings caused by ambiguity and sarcasm, we should consider multimodal signals including textual, visual and acoustic signals. The crucial challenge is to fuse different modalities of features for sentiment analysis. To effectively fuse the information carried by different modalities and better predict the sentiments, we design a novel multi-head attention based"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2103.02362","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2021-03-03T12:30:11Z","cross_cats_sorted":[],"title_canon_sha256":"1b949b264d9b773611435d67e4c772aeb2bf99757532e943228ae34ecb84f577","abstract_canon_sha256":"920a0440b78d66d5ea58dea616aba29b17cbfa004c68eb2d91e1170be978eab6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:31:58.201827Z","signature_b64":"wuwYKVA3LzFvWHD9eZVVxMO0sXZbsseiKAZlezNlp/RqFgkWhDBh3bYfGYsHSzS1t0KyRVOdWpHhwATDkcSPBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"43f8e9bdcc2964446f87bfe8573f4e4471898f7707710850366bcc10091bea89","last_reissued_at":"2026-07-05T03:31:58.201364Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:31:58.201364Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Video Sentiment Analysis with Bimodal Information-augmented Multi-Head Attention","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Chuanshuai Ma, Huiran Zhang, Junjie Peng, Ting Wu, Wenqiang Zhang, Yansong Huang","submitted_at":"2021-03-03T12:30:11Z","abstract_excerpt":"Humans express feelings or emotions via different channels. Take language as an example, it entails different sentiments under different visual-acoustic contexts. To precisely understand human intentions as well as reduce the misunderstandings caused by ambiguity and sarcasm, we should consider multimodal signals including textual, visual and acoustic signals. The crucial challenge is to fuse different modalities of features for sentiment analysis. To effectively fuse the information carried by different modalities and better predict the sentiments, we design a novel multi-head attention based"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2103.02362","kind":"arxiv","version":3},"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/2103.02362/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2103.02362","created_at":"2026-07-05T03:31:58.201423+00:00"},{"alias_kind":"arxiv_version","alias_value":"2103.02362v3","created_at":"2026-07-05T03:31:58.201423+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2103.02362","created_at":"2026-07-05T03:31:58.201423+00:00"},{"alias_kind":"pith_short_12","alias_value":"IP4OTPOMFFSE","created_at":"2026-07-05T03:31:58.201423+00:00"},{"alias_kind":"pith_short_16","alias_value":"IP4OTPOMFFSEI34H","created_at":"2026-07-05T03:31:58.201423+00:00"},{"alias_kind":"pith_short_8","alias_value":"IP4OTPOM","created_at":"2026-07-05T03:31:58.201423+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/IP4OTPOMFFSEI34HX7UFOP2OIR","json":"https://pith.science/pith/IP4OTPOMFFSEI34HX7UFOP2OIR.json","graph_json":"https://pith.science/api/pith-number/IP4OTPOMFFSEI34HX7UFOP2OIR/graph.json","events_json":"https://pith.science/api/pith-number/IP4OTPOMFFSEI34HX7UFOP2OIR/events.json","paper":"https://pith.science/paper/IP4OTPOM"},"agent_actions":{"view_html":"https://pith.science/pith/IP4OTPOMFFSEI34HX7UFOP2OIR","download_json":"https://pith.science/pith/IP4OTPOMFFSEI34HX7UFOP2OIR.json","view_paper":"https://pith.science/paper/IP4OTPOM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2103.02362&json=true","fetch_graph":"https://pith.science/api/pith-number/IP4OTPOMFFSEI34HX7UFOP2OIR/graph.json","fetch_events":"https://pith.science/api/pith-number/IP4OTPOMFFSEI34HX7UFOP2OIR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IP4OTPOMFFSEI34HX7UFOP2OIR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IP4OTPOMFFSEI34HX7UFOP2OIR/action/storage_attestation","attest_author":"https://pith.science/pith/IP4OTPOMFFSEI34HX7UFOP2OIR/action/author_attestation","sign_citation":"https://pith.science/pith/IP4OTPOMFFSEI34HX7UFOP2OIR/action/citation_signature","submit_replication":"https://pith.science/pith/IP4OTPOMFFSEI34HX7UFOP2OIR/action/replication_record"}},"created_at":"2026-07-05T03:31:58.201423+00:00","updated_at":"2026-07-05T03:31:58.201423+00:00"}