{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:FXIU6OTDRTAIJ77U7JUCUN4MN5","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":"232173b4474d449b563d3d06bb0e6fc6d358b1d2f4f665a3d66442cc4401072b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-10-12T23:38:57Z","title_canon_sha256":"78027486394fa34ce89d3234fee78083135767fd1c8d7a7d6b22cdb0da61580d"},"schema_version":"1.0","source":{"id":"2210.06629","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.06629","created_at":"2026-07-05T06:19:37Z"},{"alias_kind":"arxiv_version","alias_value":"2210.06629v2","created_at":"2026-07-05T06:19:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.06629","created_at":"2026-07-05T06:19:37Z"},{"alias_kind":"pith_short_12","alias_value":"FXIU6OTDRTAI","created_at":"2026-07-05T06:19:37Z"},{"alias_kind":"pith_short_16","alias_value":"FXIU6OTDRTAIJ77U","created_at":"2026-07-05T06:19:37Z"},{"alias_kind":"pith_short_8","alias_value":"FXIU6OTD","created_at":"2026-07-05T06:19:37Z"}],"graph_snapshots":[{"event_id":"sha256:daeb050882781d6fbdfa18520db592f6feb901d09a18a060ceaede0f7464db85","target":"graph","created_at":"2026-07-05T06:19:37Z","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/2210.06629/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Aspect-based Sentiment Analysis (ABSA) is a fine-grained sentiment analysis task which involves four elements from user-generated texts: aspect term, aspect category, opinion term, and sentiment polarity. Most computational approaches focus on some of the ABSA sub-tasks such as tuple (aspect term, sentiment polarity) or triplet (aspect term, opinion term, sentiment polarity) extraction using either pipeline or joint modeling approaches. Recently, generative approaches have been proposed to extract all four elements as (one or more) quadruplets from text as a single task. In this work, we take ","authors_text":"Dan Roth, Kishaloy Halder, Miguel Ballesteros, Neha Anna John, Rishita Anubhai, Robert Vacareanu, Shuai Wang, Siddharth Varia, Smaranda Muresan, Yassine Benajiba","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-10-12T23:38:57Z","title":"Instruction Tuning for Few-Shot Aspect-Based Sentiment Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.06629","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":"sha256:77f976e188c5b2289f56a36720a8bb41a1eed7871ff2d8796188b59c85c471ca","target":"record","created_at":"2026-07-05T06:19:37Z","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":"232173b4474d449b563d3d06bb0e6fc6d358b1d2f4f665a3d66442cc4401072b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-10-12T23:38:57Z","title_canon_sha256":"78027486394fa34ce89d3234fee78083135767fd1c8d7a7d6b22cdb0da61580d"},"schema_version":"1.0","source":{"id":"2210.06629","kind":"arxiv","version":2}},"canonical_sha256":"2dd14f3a638cc084fff4fa682a378c6f760eec35ead7605fb35dd81824495237","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2dd14f3a638cc084fff4fa682a378c6f760eec35ead7605fb35dd81824495237","first_computed_at":"2026-07-05T06:19:37.363184Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:19:37.363184Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DaZWbsXJ8XXc6KCDFGgJg8EoZ/yeYtEsZfGXSL1vKq1RzvyPm5z5D9InUHaSsAxpLY7eycHqcPzZWdNP2K2pAA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:19:37.363676Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.06629","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:77f976e188c5b2289f56a36720a8bb41a1eed7871ff2d8796188b59c85c471ca","sha256:daeb050882781d6fbdfa18520db592f6feb901d09a18a060ceaede0f7464db85"],"state_sha256":"5074e38e8b90c7bde1536566a3998c364a50b05b29d3f9a34137dce53192d734"}