{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:2NJVF7TYO5LVSDDIBMB6FZSHYN","short_pith_number":"pith:2NJVF7TY","canonical_record":{"source":{"id":"2501.00062","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-29T05:29:52Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"dc4efc10796a6d60460a2b4bbc7a33d982e497626eab1068f86710b484ebdf18","abstract_canon_sha256":"47f29ca064717f31e0f9b7cbbf437f1cc7d5f030c47cd3b364d0c94c2538903c"},"schema_version":"1.0"},"canonical_sha256":"d35352fe787757590c680b03e2e647c3692397e1437363ac9dfcdfcbc1fd5afe","source":{"kind":"arxiv","id":"2501.00062","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.00062","created_at":"2026-07-05T10:58:21Z"},{"alias_kind":"arxiv_version","alias_value":"2501.00062v2","created_at":"2026-07-05T10:58:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.00062","created_at":"2026-07-05T10:58:21Z"},{"alias_kind":"pith_short_12","alias_value":"2NJVF7TYO5LV","created_at":"2026-07-05T10:58:21Z"},{"alias_kind":"pith_short_16","alias_value":"2NJVF7TYO5LVSDDI","created_at":"2026-07-05T10:58:21Z"},{"alias_kind":"pith_short_8","alias_value":"2NJVF7TY","created_at":"2026-07-05T10:58:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:2NJVF7TYO5LVSDDIBMB6FZSHYN","target":"record","payload":{"canonical_record":{"source":{"id":"2501.00062","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-29T05:29:52Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"dc4efc10796a6d60460a2b4bbc7a33d982e497626eab1068f86710b484ebdf18","abstract_canon_sha256":"47f29ca064717f31e0f9b7cbbf437f1cc7d5f030c47cd3b364d0c94c2538903c"},"schema_version":"1.0"},"canonical_sha256":"d35352fe787757590c680b03e2e647c3692397e1437363ac9dfcdfcbc1fd5afe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:58:21.933299Z","signature_b64":"rMqytxsCEoCcmLVaewX3hZ2VrRJLYwZYPeedFmU5v5DD2NgeU1LrWIu2SyBzwMyeiwsXkQi969fgxtM6aVFaCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d35352fe787757590c680b03e2e647c3692397e1437363ac9dfcdfcbc1fd5afe","last_reissued_at":"2026-07-05T10:58:21.932798Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:58:21.932798Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.00062","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":"2026-07-05T10:58:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0stzKaE+5TcUW5UzjGzDkP0FWgmRUCMJhsT59Eq6H854RfcrTkNLw4GPGqo2Bjf33pNagPJFl7LM1CiwZSiBCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T16:25:04.391783Z"},"content_sha256":"3f64fcfabd7fe7491818e0b893361e26bfb5c41f2c385ca3a379fc8690cd438d","schema_version":"1.0","event_id":"sha256:3f64fcfabd7fe7491818e0b893361e26bfb5c41f2c385ca3a379fc8690cd438d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:2NJVF7TYO5LVSDDIBMB6FZSHYN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"James P. Beno","submitted_at":"2024-12-29T05:29:52Z","abstract_excerpt":"Bidirectional transformers excel at sentiment analysis, and Large Language Models (LLM) are effective zero-shot learners. Might they perform better as a team? This paper explores collaborative approaches between ELECTRA and GPT-4o for three-way sentiment classification. We fine-tuned (FT) four models (ELECTRA Base/Large, GPT-4o/4o-mini) using a mix of reviews from Stanford Sentiment Treebank (SST) and DynaSent. We provided input from ELECTRA to GPT as: predicted label, probabilities, and retrieved examples. Sharing ELECTRA Base FT predictions with GPT-4o-mini significantly improved performance"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.00062","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/2501.00062/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":"2026-07-05T10:58:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yGLuzq0fByrKWoWXY4XkoeWppvlu0lHk0vCt0R8+tSA5aj1mDDtnovyL6wy/invpn5pR/M0TZ6Xsf6RIfYLNAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T16:25:04.392164Z"},"content_sha256":"6b118419e1a7e67059e18f323316403790aa34d0af9e976bea6370f460118010","schema_version":"1.0","event_id":"sha256:6b118419e1a7e67059e18f323316403790aa34d0af9e976bea6370f460118010"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2NJVF7TYO5LVSDDIBMB6FZSHYN/bundle.json","state_url":"https://pith.science/pith/2NJVF7TYO5LVSDDIBMB6FZSHYN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2NJVF7TYO5LVSDDIBMB6FZSHYN/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":"2026-08-07T16:25:04Z","links":{"resolver":"https://pith.science/pith/2NJVF7TYO5LVSDDIBMB6FZSHYN","bundle":"https://pith.science/pith/2NJVF7TYO5LVSDDIBMB6FZSHYN/bundle.json","state":"https://pith.science/pith/2NJVF7TYO5LVSDDIBMB6FZSHYN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2NJVF7TYO5LVSDDIBMB6FZSHYN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:2NJVF7TYO5LVSDDIBMB6FZSHYN","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":"47f29ca064717f31e0f9b7cbbf437f1cc7d5f030c47cd3b364d0c94c2538903c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-29T05:29:52Z","title_canon_sha256":"dc4efc10796a6d60460a2b4bbc7a33d982e497626eab1068f86710b484ebdf18"},"schema_version":"1.0","source":{"id":"2501.00062","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.00062","created_at":"2026-07-05T10:58:21Z"},{"alias_kind":"arxiv_version","alias_value":"2501.00062v2","created_at":"2026-07-05T10:58:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.00062","created_at":"2026-07-05T10:58:21Z"},{"alias_kind":"pith_short_12","alias_value":"2NJVF7TYO5LV","created_at":"2026-07-05T10:58:21Z"},{"alias_kind":"pith_short_16","alias_value":"2NJVF7TYO5LVSDDI","created_at":"2026-07-05T10:58:21Z"},{"alias_kind":"pith_short_8","alias_value":"2NJVF7TY","created_at":"2026-07-05T10:58:21Z"}],"graph_snapshots":[{"event_id":"sha256:6b118419e1a7e67059e18f323316403790aa34d0af9e976bea6370f460118010","target":"graph","created_at":"2026-07-05T10:58:21Z","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/2501.00062/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Bidirectional transformers excel at sentiment analysis, and Large Language Models (LLM) are effective zero-shot learners. Might they perform better as a team? This paper explores collaborative approaches between ELECTRA and GPT-4o for three-way sentiment classification. We fine-tuned (FT) four models (ELECTRA Base/Large, GPT-4o/4o-mini) using a mix of reviews from Stanford Sentiment Treebank (SST) and DynaSent. We provided input from ELECTRA to GPT as: predicted label, probabilities, and retrieved examples. Sharing ELECTRA Base FT predictions with GPT-4o-mini significantly improved performance","authors_text":"James P. Beno","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-29T05:29:52Z","title":"ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.00062","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":"sha256:3f64fcfabd7fe7491818e0b893361e26bfb5c41f2c385ca3a379fc8690cd438d","target":"record","created_at":"2026-07-05T10:58:21Z","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":"47f29ca064717f31e0f9b7cbbf437f1cc7d5f030c47cd3b364d0c94c2538903c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-29T05:29:52Z","title_canon_sha256":"dc4efc10796a6d60460a2b4bbc7a33d982e497626eab1068f86710b484ebdf18"},"schema_version":"1.0","source":{"id":"2501.00062","kind":"arxiv","version":2}},"canonical_sha256":"d35352fe787757590c680b03e2e647c3692397e1437363ac9dfcdfcbc1fd5afe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d35352fe787757590c680b03e2e647c3692397e1437363ac9dfcdfcbc1fd5afe","first_computed_at":"2026-07-05T10:58:21.932798Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:58:21.932798Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rMqytxsCEoCcmLVaewX3hZ2VrRJLYwZYPeedFmU5v5DD2NgeU1LrWIu2SyBzwMyeiwsXkQi969fgxtM6aVFaCw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:58:21.933299Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.00062","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3f64fcfabd7fe7491818e0b893361e26bfb5c41f2c385ca3a379fc8690cd438d","sha256:6b118419e1a7e67059e18f323316403790aa34d0af9e976bea6370f460118010"],"state_sha256":"36540ff2469b7f8176b453f13d77b475cea7d7ac5c649b3f322ca3a9e1031875"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EyvQ86b5tX8FU2gbUIL3XpD7pXLa8uMeYKK8Dd/F1f8XKwnss2ZCalXDpEhAHvJ4u18xGAiVqimtW1faYW4WCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T16:25:04.395165Z","bundle_sha256":"f47f5ce8f020a66beb087fcf7911d7cc90aa8c75e1f95231263e041468135d27"}}