{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ZFB7OTAVULBQPHSLKZCKIZ5QVY","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":"fb0bbe2ee6c3205c0f831ffb2860565b16dc2f1839ac564428b80d7039bfc029","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-09T06:47:42Z","title_canon_sha256":"28d9d8fb00842deb7ff8490f28ba5a3574a9df39dd7e9fbe0463bf1e0edcf7d6"},"schema_version":"1.0","source":{"id":"2412.06249","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.06249","created_at":"2026-07-05T09:46:17Z"},{"alias_kind":"arxiv_version","alias_value":"2412.06249v1","created_at":"2026-07-05T09:46:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.06249","created_at":"2026-07-05T09:46:17Z"},{"alias_kind":"pith_short_12","alias_value":"ZFB7OTAVULBQ","created_at":"2026-07-05T09:46:17Z"},{"alias_kind":"pith_short_16","alias_value":"ZFB7OTAVULBQPHSL","created_at":"2026-07-05T09:46:17Z"},{"alias_kind":"pith_short_8","alias_value":"ZFB7OTAV","created_at":"2026-07-05T09:46:17Z"}],"graph_snapshots":[{"event_id":"sha256:3596c488cee047bc5621767703d7d4be340145b9078f851f173813f43b2b94dc","target":"graph","created_at":"2026-07-05T09:46:17Z","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/2412.06249/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study aims to explore the performance improvement method of large language models based on GPT-4 under the multi-task learning framework and conducts experiments on two tasks: text classification and automatic summary generation. Through the combined design of shared feature extractors and task-specific modules, we achieve knowledge-sharing and optimization of multiple tasks in the same model. The experiment uses multiple subtasks of the GLUE dataset to compare the performance of the multi-task model with the single-task GPT-4, the multi-task version of GPT-3, the BERT basic model, and th","authors_text":"Bingying Liu, Chihang Wang, Hongye Zheng, Jiajing Chen, Shuo Wang, Zhen Qi","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-09T06:47:42Z","title":"Optimizing Multi-Task Learning for Enhanced Performance in Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.06249","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":"sha256:0ad6052f31f504a72a6051af1fc4d7dc3e746904802612ee7ab625d4830c0b8d","target":"record","created_at":"2026-07-05T09:46:17Z","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":"fb0bbe2ee6c3205c0f831ffb2860565b16dc2f1839ac564428b80d7039bfc029","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-09T06:47:42Z","title_canon_sha256":"28d9d8fb00842deb7ff8490f28ba5a3574a9df39dd7e9fbe0463bf1e0edcf7d6"},"schema_version":"1.0","source":{"id":"2412.06249","kind":"arxiv","version":1}},"canonical_sha256":"c943f74c15a2c3079e4b5644a467b0ae3372410c13c0435559132a1128381bcb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c943f74c15a2c3079e4b5644a467b0ae3372410c13c0435559132a1128381bcb","first_computed_at":"2026-07-05T09:46:17.899088Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:46:17.899088Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AoL/5Hk9lkTnvStBOseuV9GRqpUk4vi1hox809D+DEvQ0E7Qj5R79SEdW2aWh+9m3zoTQSOT/36NvI0gCtYKBw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:46:17.899570Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.06249","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0ad6052f31f504a72a6051af1fc4d7dc3e746904802612ee7ab625d4830c0b8d","sha256:3596c488cee047bc5621767703d7d4be340145b9078f851f173813f43b2b94dc"],"state_sha256":"ebf0ce909dc0e19e951cd3327505fe835f2022ec165ad02d152b8c65becb7d2e"}