{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:DAUDCQJWROS2EB3QDS46TUVGMF","short_pith_number":"pith:DAUDCQJW","canonical_record":{"source":{"id":"2405.18035","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-05-28T10:39:10Z","cross_cats_sorted":[],"title_canon_sha256":"dd6bf81fcd3743ff8f72bf7b4d09434cc57c411cb7d850884ee34da3f18e7e50","abstract_canon_sha256":"6b1e63518c284cc87946ace76ac0236812b6446c7badf2034fa978bec8863d6e"},"schema_version":"1.0"},"canonical_sha256":"18283141368ba5a207701cb9e9d2a6616e6a6e1bd4590bf07e1875ac01d704a2","source":{"kind":"arxiv","id":"2405.18035","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.18035","created_at":"2026-07-05T08:24:25Z"},{"alias_kind":"arxiv_version","alias_value":"2405.18035v2","created_at":"2026-07-05T08:24:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.18035","created_at":"2026-07-05T08:24:25Z"},{"alias_kind":"pith_short_12","alias_value":"DAUDCQJWROS2","created_at":"2026-07-05T08:24:25Z"},{"alias_kind":"pith_short_16","alias_value":"DAUDCQJWROS2EB3Q","created_at":"2026-07-05T08:24:25Z"},{"alias_kind":"pith_short_8","alias_value":"DAUDCQJW","created_at":"2026-07-05T08:24:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:DAUDCQJWROS2EB3QDS46TUVGMF","target":"record","payload":{"canonical_record":{"source":{"id":"2405.18035","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-05-28T10:39:10Z","cross_cats_sorted":[],"title_canon_sha256":"dd6bf81fcd3743ff8f72bf7b4d09434cc57c411cb7d850884ee34da3f18e7e50","abstract_canon_sha256":"6b1e63518c284cc87946ace76ac0236812b6446c7badf2034fa978bec8863d6e"},"schema_version":"1.0"},"canonical_sha256":"18283141368ba5a207701cb9e9d2a6616e6a6e1bd4590bf07e1875ac01d704a2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:24:25.604458Z","signature_b64":"pjzIUZ5N0gdnVr9fUMrd10p9EEtmrgeT4aR/jXtbjVmMQ3COqrIvUyW8dJ80vLY3ZUbaW0cFCqx1QdZOos/FDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"18283141368ba5a207701cb9e9d2a6616e6a6e1bd4590bf07e1875ac01d704a2","last_reissued_at":"2026-07-05T08:24:25.604039Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:24:25.604039Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.18035","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":"2026-07-05T08:24:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"op8a+tBNax6qjF1CGCC5BJwxc0kttLIdzi3cV09iHKru0zqt2k6aCdVSVWVwhAG4PZ1m3IxAkiypT2iCaTkIAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T00:08:33.465956Z"},"content_sha256":"6faccf77674108818081a92477581d558b7d2284c7d3266977d03c6baf8abe89","schema_version":"1.0","event_id":"sha256:6faccf77674108818081a92477581d558b7d2284c7d3266977d03c6baf8abe89"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:DAUDCQJWROS2EB3QDS46TUVGMF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Instruction Tuning with Retrieval-based Examples Ranking for Aspect-based Sentiment Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Guangmin Zheng, Jin Wang, Liang-Chih Yu, Xuejie Zhang","submitted_at":"2024-05-28T10:39:10Z","abstract_excerpt":"Aspect-based sentiment analysis (ABSA) identifies sentiment information related to specific aspects and provides deeper market insights to businesses and organizations. With the emergence of large language models (LMs), recent studies have proposed using fixed examples for instruction tuning to reformulate ABSA as a generation task. However, the performance is sensitive to the selection of in-context examples; several retrieval methods are based on surface similarity and are independent of the LM generative objective. This study proposes an instruction learning method with retrieval-based exam"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.18035","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/2405.18035/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":"2026-07-05T08:24:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"19eKrwl+6DoXdko7vd+mw2TZrKi+zwO0pZRZ8tyjGM1LV0bgZIpUXo+cFtTiT+bdpRyV2IHBjGkUFH8M/Nn0Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T00:08:33.466802Z"},"content_sha256":"d59064189fd57bb8cabc7d52b98552db644c5fa3d917af1bb020279330e65dd5","schema_version":"1.0","event_id":"sha256:d59064189fd57bb8cabc7d52b98552db644c5fa3d917af1bb020279330e65dd5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DAUDCQJWROS2EB3QDS46TUVGMF/bundle.json","state_url":"https://pith.science/pith/DAUDCQJWROS2EB3QDS46TUVGMF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DAUDCQJWROS2EB3QDS46TUVGMF/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":"2026-08-05T00:08:33Z","links":{"resolver":"https://pith.science/pith/DAUDCQJWROS2EB3QDS46TUVGMF","bundle":"https://pith.science/pith/DAUDCQJWROS2EB3QDS46TUVGMF/bundle.json","state":"https://pith.science/pith/DAUDCQJWROS2EB3QDS46TUVGMF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DAUDCQJWROS2EB3QDS46TUVGMF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:DAUDCQJWROS2EB3QDS46TUVGMF","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":"6b1e63518c284cc87946ace76ac0236812b6446c7badf2034fa978bec8863d6e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-05-28T10:39:10Z","title_canon_sha256":"dd6bf81fcd3743ff8f72bf7b4d09434cc57c411cb7d850884ee34da3f18e7e50"},"schema_version":"1.0","source":{"id":"2405.18035","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.18035","created_at":"2026-07-05T08:24:25Z"},{"alias_kind":"arxiv_version","alias_value":"2405.18035v2","created_at":"2026-07-05T08:24:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.18035","created_at":"2026-07-05T08:24:25Z"},{"alias_kind":"pith_short_12","alias_value":"DAUDCQJWROS2","created_at":"2026-07-05T08:24:25Z"},{"alias_kind":"pith_short_16","alias_value":"DAUDCQJWROS2EB3Q","created_at":"2026-07-05T08:24:25Z"},{"alias_kind":"pith_short_8","alias_value":"DAUDCQJW","created_at":"2026-07-05T08:24:25Z"}],"graph_snapshots":[{"event_id":"sha256:d59064189fd57bb8cabc7d52b98552db644c5fa3d917af1bb020279330e65dd5","target":"graph","created_at":"2026-07-05T08:24:25Z","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/2405.18035/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Aspect-based sentiment analysis (ABSA) identifies sentiment information related to specific aspects and provides deeper market insights to businesses and organizations. With the emergence of large language models (LMs), recent studies have proposed using fixed examples for instruction tuning to reformulate ABSA as a generation task. However, the performance is sensitive to the selection of in-context examples; several retrieval methods are based on surface similarity and are independent of the LM generative objective. This study proposes an instruction learning method with retrieval-based exam","authors_text":"Guangmin Zheng, Jin Wang, Liang-Chih Yu, Xuejie Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-05-28T10:39:10Z","title":"Instruction Tuning with Retrieval-based Examples Ranking for Aspect-based Sentiment Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.18035","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":"sha256:6faccf77674108818081a92477581d558b7d2284c7d3266977d03c6baf8abe89","target":"record","created_at":"2026-07-05T08:24:25Z","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":"6b1e63518c284cc87946ace76ac0236812b6446c7badf2034fa978bec8863d6e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-05-28T10:39:10Z","title_canon_sha256":"dd6bf81fcd3743ff8f72bf7b4d09434cc57c411cb7d850884ee34da3f18e7e50"},"schema_version":"1.0","source":{"id":"2405.18035","kind":"arxiv","version":2}},"canonical_sha256":"18283141368ba5a207701cb9e9d2a6616e6a6e1bd4590bf07e1875ac01d704a2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"18283141368ba5a207701cb9e9d2a6616e6a6e1bd4590bf07e1875ac01d704a2","first_computed_at":"2026-07-05T08:24:25.604039Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:24:25.604039Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pjzIUZ5N0gdnVr9fUMrd10p9EEtmrgeT4aR/jXtbjVmMQ3COqrIvUyW8dJ80vLY3ZUbaW0cFCqx1QdZOos/FDA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:24:25.604458Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.18035","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6faccf77674108818081a92477581d558b7d2284c7d3266977d03c6baf8abe89","sha256:d59064189fd57bb8cabc7d52b98552db644c5fa3d917af1bb020279330e65dd5"],"state_sha256":"e5cb4104199f545e6f5a6d5df8aa1bfc5d6798e3bb8d0cff7aa07638f30b3a4f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hwsWgoLXaDp/6vKpkb9WQHpTs181niHtcLXMbN1FZQQfUo4utepKS1di2lXdxkpuX5dr9KKLoXPUMydPDI43Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T00:08:33.472481Z","bundle_sha256":"56de6fa422f8a384b0f6844f57a28cb107319a8564fa40892afd4f305c163d97"}}