{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:XKQIAPZDSUW43RBZISWPQXR6YJ","short_pith_number":"pith:XKQIAPZD","canonical_record":{"source":{"id":"2203.16369","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-03-30T14:48:46Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1bc849c6e57b3ec657fb6ba739475bce0074ef796ff7069e45cc1a6f035a3d64","abstract_canon_sha256":"7a33a555030cfcf455c22cf65fbc274a7142e87fd7e84fcd5087d67026bbb360"},"schema_version":"1.0"},"canonical_sha256":"baa0803f23952dcdc43944acf85e3ec26ce3d25fb36401121f486436d2171825","source":{"kind":"arxiv","id":"2203.16369","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.16369","created_at":"2026-07-05T05:18:46Z"},{"alias_kind":"arxiv_version","alias_value":"2203.16369v2","created_at":"2026-07-05T05:18:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.16369","created_at":"2026-07-05T05:18:46Z"},{"alias_kind":"pith_short_12","alias_value":"XKQIAPZDSUW4","created_at":"2026-07-05T05:18:46Z"},{"alias_kind":"pith_short_16","alias_value":"XKQIAPZDSUW43RBZ","created_at":"2026-07-05T05:18:46Z"},{"alias_kind":"pith_short_8","alias_value":"XKQIAPZD","created_at":"2026-07-05T05:18:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:XKQIAPZDSUW43RBZISWPQXR6YJ","target":"record","payload":{"canonical_record":{"source":{"id":"2203.16369","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-03-30T14:48:46Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1bc849c6e57b3ec657fb6ba739475bce0074ef796ff7069e45cc1a6f035a3d64","abstract_canon_sha256":"7a33a555030cfcf455c22cf65fbc274a7142e87fd7e84fcd5087d67026bbb360"},"schema_version":"1.0"},"canonical_sha256":"baa0803f23952dcdc43944acf85e3ec26ce3d25fb36401121f486436d2171825","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:18:46.283634Z","signature_b64":"saYdohlFZ+/8amgVPI/8VM/iOubFQTRU/i0x4FzHv/UNi1Kgznhen3UJHRR/aeGydIXUMJsG+EXsDz6/DLhHAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"baa0803f23952dcdc43944acf85e3ec26ce3d25fb36401121f486436d2171825","last_reissued_at":"2026-07-05T05:18:46.283171Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:18:46.283171Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.16369","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":"2026-07-05T05:18:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+7hN0p+9gdgu1aYWWlVieLd7OXSIfEIy/4fcEM4nI6tZWgIwiU0s5pwQ01sw7RSbuazrWeHBHXF3RRDMoVQBDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T11:31:20.073286Z"},"content_sha256":"d4170e09ffb27b78b062a8fbe56fcee818ffbcb9883194d1da22476bd7eb2a80","schema_version":"1.0","event_id":"sha256:d4170e09ffb27b78b062a8fbe56fcee818ffbcb9883194d1da22476bd7eb2a80"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:XKQIAPZDSUW43RBZISWPQXR6YJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Incorporating Dynamic Semantics into Pre-Trained Language Model for Aspect-based Sentiment Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Enhong Chen, Hongke Zhao, Kai Zhang, Kun Zhang, Mengdi Zhang, Qi Liu, Wei Wu","submitted_at":"2022-03-30T14:48:46Z","abstract_excerpt":"Aspect-based sentiment analysis (ABSA) predicts sentiment polarity towards a specific aspect in the given sentence. While pre-trained language models such as BERT have achieved great success, incorporating dynamic semantic changes into ABSA remains challenging. To this end, in this paper, we propose to address this problem by Dynamic Re-weighting BERT (DR-BERT), a novel method designed to learn dynamic aspect-oriented semantics for ABSA. Specifically, we first take the Stack-BERT layers as a primary encoder to grasp the overall semantic of the sentence and then fine-tune it by incorporating a "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.16369","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2203.16369/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":"2026-07-05T05:18:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rDfixsr6nlv6OHNQlgH3pzsO6drwQcLbkjtBDKGePhJkY2SXSQC2RoLAON6guFRn7yJfW0fm0mBwqQIpjFdcCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T11:31:20.073610Z"},"content_sha256":"3a1fb7bd1e4235529b4a9f5ba1779adcfa6f29ee4a79a039ad27ea5cb798f491","schema_version":"1.0","event_id":"sha256:3a1fb7bd1e4235529b4a9f5ba1779adcfa6f29ee4a79a039ad27ea5cb798f491"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XKQIAPZDSUW43RBZISWPQXR6YJ/bundle.json","state_url":"https://pith.science/pith/XKQIAPZDSUW43RBZISWPQXR6YJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XKQIAPZDSUW43RBZISWPQXR6YJ/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":"2026-08-11T11:31:20Z","links":{"resolver":"https://pith.science/pith/XKQIAPZDSUW43RBZISWPQXR6YJ","bundle":"https://pith.science/pith/XKQIAPZDSUW43RBZISWPQXR6YJ/bundle.json","state":"https://pith.science/pith/XKQIAPZDSUW43RBZISWPQXR6YJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XKQIAPZDSUW43RBZISWPQXR6YJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:XKQIAPZDSUW43RBZISWPQXR6YJ","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":"7a33a555030cfcf455c22cf65fbc274a7142e87fd7e84fcd5087d67026bbb360","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-03-30T14:48:46Z","title_canon_sha256":"1bc849c6e57b3ec657fb6ba739475bce0074ef796ff7069e45cc1a6f035a3d64"},"schema_version":"1.0","source":{"id":"2203.16369","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.16369","created_at":"2026-07-05T05:18:46Z"},{"alias_kind":"arxiv_version","alias_value":"2203.16369v2","created_at":"2026-07-05T05:18:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.16369","created_at":"2026-07-05T05:18:46Z"},{"alias_kind":"pith_short_12","alias_value":"XKQIAPZDSUW4","created_at":"2026-07-05T05:18:46Z"},{"alias_kind":"pith_short_16","alias_value":"XKQIAPZDSUW43RBZ","created_at":"2026-07-05T05:18:46Z"},{"alias_kind":"pith_short_8","alias_value":"XKQIAPZD","created_at":"2026-07-05T05:18:46Z"}],"graph_snapshots":[{"event_id":"sha256:3a1fb7bd1e4235529b4a9f5ba1779adcfa6f29ee4a79a039ad27ea5cb798f491","target":"graph","created_at":"2026-07-05T05:18:46Z","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/2203.16369/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Aspect-based sentiment analysis (ABSA) predicts sentiment polarity towards a specific aspect in the given sentence. While pre-trained language models such as BERT have achieved great success, incorporating dynamic semantic changes into ABSA remains challenging. To this end, in this paper, we propose to address this problem by Dynamic Re-weighting BERT (DR-BERT), a novel method designed to learn dynamic aspect-oriented semantics for ABSA. Specifically, we first take the Stack-BERT layers as a primary encoder to grasp the overall semantic of the sentence and then fine-tune it by incorporating a ","authors_text":"Enhong Chen, Hongke Zhao, Kai Zhang, Kun Zhang, Mengdi Zhang, Qi Liu, Wei Wu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-03-30T14:48:46Z","title":"Incorporating Dynamic Semantics into Pre-Trained Language Model for Aspect-based Sentiment Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.16369","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:d4170e09ffb27b78b062a8fbe56fcee818ffbcb9883194d1da22476bd7eb2a80","target":"record","created_at":"2026-07-05T05:18:46Z","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":"7a33a555030cfcf455c22cf65fbc274a7142e87fd7e84fcd5087d67026bbb360","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-03-30T14:48:46Z","title_canon_sha256":"1bc849c6e57b3ec657fb6ba739475bce0074ef796ff7069e45cc1a6f035a3d64"},"schema_version":"1.0","source":{"id":"2203.16369","kind":"arxiv","version":2}},"canonical_sha256":"baa0803f23952dcdc43944acf85e3ec26ce3d25fb36401121f486436d2171825","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"baa0803f23952dcdc43944acf85e3ec26ce3d25fb36401121f486436d2171825","first_computed_at":"2026-07-05T05:18:46.283171Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:18:46.283171Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"saYdohlFZ+/8amgVPI/8VM/iOubFQTRU/i0x4FzHv/UNi1Kgznhen3UJHRR/aeGydIXUMJsG+EXsDz6/DLhHAw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:18:46.283634Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.16369","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d4170e09ffb27b78b062a8fbe56fcee818ffbcb9883194d1da22476bd7eb2a80","sha256:3a1fb7bd1e4235529b4a9f5ba1779adcfa6f29ee4a79a039ad27ea5cb798f491"],"state_sha256":"c665fca43da963e508c7f33e4a20e29e99103b5fa2ff50349a7a6a9aff95c95d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JcBMhKmI8sHLrbMRZpLCOPfojnVEpk4EGQQS0kuAv1Hch0PK13VEbcCKKlNc/pNhfudBXiLoyI44AYxHy0K2Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T11:31:20.076252Z","bundle_sha256":"9f12c0f03a25bea9d3a6f2be3bfbadf189cf5b7fab70cdffa1a245602d1208dc"}}