{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:EAYU4YINFNNGUZKDW7ZTWD3STI","short_pith_number":"pith:EAYU4YIN","canonical_record":{"source":{"id":"1908.06264","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-17T08:59:51Z","cross_cats_sorted":[],"title_canon_sha256":"289d75bc5db0be3f3d31f81b4351573898211ba1a61dec86978b95e3f1d8dbda","abstract_canon_sha256":"4936798c15a2413cf6f5ca1ed0d018eff7f0217465f0e4e596a8212999d7dfc9"},"schema_version":"1.0"},"canonical_sha256":"20314e610d2b5a6a6543b7f33b0f729a34c259acc626c6a9a02ece49e793bfa0","source":{"kind":"arxiv","id":"1908.06264","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.06264","created_at":"2026-07-04T23:58:14Z"},{"alias_kind":"arxiv_version","alias_value":"1908.06264v1","created_at":"2026-07-04T23:58:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.06264","created_at":"2026-07-04T23:58:14Z"},{"alias_kind":"pith_short_12","alias_value":"EAYU4YINFNNG","created_at":"2026-07-04T23:58:14Z"},{"alias_kind":"pith_short_16","alias_value":"EAYU4YINFNNGUZKD","created_at":"2026-07-04T23:58:14Z"},{"alias_kind":"pith_short_8","alias_value":"EAYU4YIN","created_at":"2026-07-04T23:58:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:EAYU4YINFNNGUZKDW7ZTWD3STI","target":"record","payload":{"canonical_record":{"source":{"id":"1908.06264","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-17T08:59:51Z","cross_cats_sorted":[],"title_canon_sha256":"289d75bc5db0be3f3d31f81b4351573898211ba1a61dec86978b95e3f1d8dbda","abstract_canon_sha256":"4936798c15a2413cf6f5ca1ed0d018eff7f0217465f0e4e596a8212999d7dfc9"},"schema_version":"1.0"},"canonical_sha256":"20314e610d2b5a6a6543b7f33b0f729a34c259acc626c6a9a02ece49e793bfa0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:58:14.022699Z","signature_b64":"t92M9WBEnp7FLuJP8Qih2bzYHM6qlJyK4RbAtzDPRVU8yCoRzj1smb6r3PchoZsI6u29xixfzsG8A3YjLwjXAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"20314e610d2b5a6a6543b7f33b0f729a34c259acc626c6a9a02ece49e793bfa0","last_reissued_at":"2026-07-04T23:58:14.022225Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:58:14.022225Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1908.06264","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":"2026-07-04T23:58:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LBhvuKzGywmIWY7zHOjRQbGFbG9q/Ybs2ZLDq8lsRxji0o7gve2FrU5R7Zy+FMHxaZudaKoREXK9Dkw+RORBCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T22:52:07.793521Z"},"content_sha256":"32e28f616a9e1c9c5fce849bc88c44b74bc755f080fcaad3c34624e88616ceef","schema_version":"1.0","event_id":"sha256:32e28f616a9e1c9c5fce849bc88c44b74bc755f080fcaad3c34624e88616ceef"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:EAYU4YINFNNGUZKDW7ZTWD3STI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EmotionX-IDEA: Emotion BERT -- an Affectional Model for Conversation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Mau-Yun Ma, Ssu-Rui Lee, Ya-Wen Yu, Yen-Hao Huang, Yi-Hsin Chen, Yi-Shin Chen","submitted_at":"2019-08-17T08:59:51Z","abstract_excerpt":"In this paper, we investigate the emotion recognition ability of the pre-training language model, namely BERT. By the nature of the framework of BERT, a two-sentence structure, we adapt BERT to continues dialogue emotion prediction tasks, which rely heavily on the sentence-level context-aware understanding. The experiments show that by mapping the continues dialogue into a causal utterance pair, which is constructed by the utterance and the reply utterance, models can better capture the emotions of the reply utterance. The present method has achieved 0.815 and 0.885 micro F1 score in the testi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.06264","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/1908.06264/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":"2026-07-04T23:58:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vVu+ZbYi5u8uGthTljNQccq4QUMo/z8qeBHQ7r21+JCEsAxETDwy7gLsl4zHImpPI+t/jhT5K30EQEV6S2wnAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T22:52:07.794036Z"},"content_sha256":"5168adf1ab0249d36771be17a2c6f1fb06635b18028b0ea3abdca51ebaeee609","schema_version":"1.0","event_id":"sha256:5168adf1ab0249d36771be17a2c6f1fb06635b18028b0ea3abdca51ebaeee609"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EAYU4YINFNNGUZKDW7ZTWD3STI/bundle.json","state_url":"https://pith.science/pith/EAYU4YINFNNGUZKDW7ZTWD3STI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EAYU4YINFNNGUZKDW7ZTWD3STI/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":"2026-08-18T22:52:07Z","links":{"resolver":"https://pith.science/pith/EAYU4YINFNNGUZKDW7ZTWD3STI","bundle":"https://pith.science/pith/EAYU4YINFNNGUZKDW7ZTWD3STI/bundle.json","state":"https://pith.science/pith/EAYU4YINFNNGUZKDW7ZTWD3STI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EAYU4YINFNNGUZKDW7ZTWD3STI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:EAYU4YINFNNGUZKDW7ZTWD3STI","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":"4936798c15a2413cf6f5ca1ed0d018eff7f0217465f0e4e596a8212999d7dfc9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-17T08:59:51Z","title_canon_sha256":"289d75bc5db0be3f3d31f81b4351573898211ba1a61dec86978b95e3f1d8dbda"},"schema_version":"1.0","source":{"id":"1908.06264","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.06264","created_at":"2026-07-04T23:58:14Z"},{"alias_kind":"arxiv_version","alias_value":"1908.06264v1","created_at":"2026-07-04T23:58:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.06264","created_at":"2026-07-04T23:58:14Z"},{"alias_kind":"pith_short_12","alias_value":"EAYU4YINFNNG","created_at":"2026-07-04T23:58:14Z"},{"alias_kind":"pith_short_16","alias_value":"EAYU4YINFNNGUZKD","created_at":"2026-07-04T23:58:14Z"},{"alias_kind":"pith_short_8","alias_value":"EAYU4YIN","created_at":"2026-07-04T23:58:14Z"}],"graph_snapshots":[{"event_id":"sha256:5168adf1ab0249d36771be17a2c6f1fb06635b18028b0ea3abdca51ebaeee609","target":"graph","created_at":"2026-07-04T23:58:14Z","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/1908.06264/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we investigate the emotion recognition ability of the pre-training language model, namely BERT. By the nature of the framework of BERT, a two-sentence structure, we adapt BERT to continues dialogue emotion prediction tasks, which rely heavily on the sentence-level context-aware understanding. The experiments show that by mapping the continues dialogue into a causal utterance pair, which is constructed by the utterance and the reply utterance, models can better capture the emotions of the reply utterance. The present method has achieved 0.815 and 0.885 micro F1 score in the testi","authors_text":"Mau-Yun Ma, Ssu-Rui Lee, Ya-Wen Yu, Yen-Hao Huang, Yi-Hsin Chen, Yi-Shin Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-17T08:59:51Z","title":"EmotionX-IDEA: Emotion BERT -- an Affectional Model for Conversation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.06264","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":"sha256:32e28f616a9e1c9c5fce849bc88c44b74bc755f080fcaad3c34624e88616ceef","target":"record","created_at":"2026-07-04T23:58:14Z","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":"4936798c15a2413cf6f5ca1ed0d018eff7f0217465f0e4e596a8212999d7dfc9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-17T08:59:51Z","title_canon_sha256":"289d75bc5db0be3f3d31f81b4351573898211ba1a61dec86978b95e3f1d8dbda"},"schema_version":"1.0","source":{"id":"1908.06264","kind":"arxiv","version":1}},"canonical_sha256":"20314e610d2b5a6a6543b7f33b0f729a34c259acc626c6a9a02ece49e793bfa0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"20314e610d2b5a6a6543b7f33b0f729a34c259acc626c6a9a02ece49e793bfa0","first_computed_at":"2026-07-04T23:58:14.022225Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:58:14.022225Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"t92M9WBEnp7FLuJP8Qih2bzYHM6qlJyK4RbAtzDPRVU8yCoRzj1smb6r3PchoZsI6u29xixfzsG8A3YjLwjXAg==","signature_status":"signed_v1","signed_at":"2026-07-04T23:58:14.022699Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.06264","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:32e28f616a9e1c9c5fce849bc88c44b74bc755f080fcaad3c34624e88616ceef","sha256:5168adf1ab0249d36771be17a2c6f1fb06635b18028b0ea3abdca51ebaeee609"],"state_sha256":"10fa3c224f44851ed521f2b7b48638a0f06821deaab3e7be690e4c412c9f8565"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5XLVFHKWh/PsSvj8ZxFy9trN0gPzbqppzCd4Ep9kfbhYUNZ0qyznqarmkJ8APxZ9eH8Xe4RMWyuHv6HtbMOxDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T22:52:07.798299Z","bundle_sha256":"185f6193e19869f918f46e2d498dfd2aed72b30a668bc1d6d50f7d9b76ce447d"}}