{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:M52OTN3TJSJPWGMCUYGLD7KSWI","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":"83389c4edf8ba2c8e9e440a9f78662c6ded2b5066e52ce2c43a1d87056993f3c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2023-12-05T03:23:36Z","title_canon_sha256":"5fb868befca71c7d84e9acb2661cf01d1289c90b4d4b0904f63a100ba7821abe"},"schema_version":"1.0","source":{"id":"2312.02461","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.02461","created_at":"2026-07-05T09:19:25Z"},{"alias_kind":"arxiv_version","alias_value":"2312.02461v3","created_at":"2026-07-05T09:19:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.02461","created_at":"2026-07-05T09:19:25Z"},{"alias_kind":"pith_short_12","alias_value":"M52OTN3TJSJP","created_at":"2026-07-05T09:19:25Z"},{"alias_kind":"pith_short_16","alias_value":"M52OTN3TJSJPWGMC","created_at":"2026-07-05T09:19:25Z"},{"alias_kind":"pith_short_8","alias_value":"M52OTN3T","created_at":"2026-07-05T09:19:25Z"}],"graph_snapshots":[{"event_id":"sha256:8144c58468da4c8136d51090b42f325d484f9362cd5cb7aea961b603f1c78226","target":"graph","created_at":"2026-07-05T09:19:25Z","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/2312.02461/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper addresses unconstrained multiobjective optimization problems where two or more continuously differentiable functions have to be minimized. We delve into the conjugate gradient methods proposed by Lucambio P\\'{e}rez and Prudente (SIAM J Optim, 28(3): 2690--2720, 2018) for such problems. Instead of the Wolfe-type line search procedure used in their work, we employ a fixed stepsize formula (or no-line-search scheme), which can mitigate the pressure of choosing stepsize caused by multiple inequalities and avoid the computational cost associated with function evaluations in specific appl","authors_text":"Liping Tang, Wang Chen, Xinmin Yang, Yong Zhao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2023-12-05T03:23:36Z","title":"Conjugate gradient methods without line search for multiobjective optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.02461","kind":"arxiv","version":3},"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":"sha256:991f722a1bcecc0639562bc224c84430573ab384408dd95eb311e8dbb660c4ba","target":"record","created_at":"2026-07-05T09:19:25Z","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":"83389c4edf8ba2c8e9e440a9f78662c6ded2b5066e52ce2c43a1d87056993f3c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2023-12-05T03:23:36Z","title_canon_sha256":"5fb868befca71c7d84e9acb2661cf01d1289c90b4d4b0904f63a100ba7821abe"},"schema_version":"1.0","source":{"id":"2312.02461","kind":"arxiv","version":3}},"canonical_sha256":"6774e9b7734c92fb1982a60cb1fd52b2259cffffd55a4af304c7a2e8a0a44061","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6774e9b7734c92fb1982a60cb1fd52b2259cffffd55a4af304c7a2e8a0a44061","first_computed_at":"2026-07-05T09:19:25.304776Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:19:25.304776Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cLM1uyProAgsBNaQCWTSH5t9hgsVlcJKJ1SCA8h7BfDp3Owjbm6bAtHCyWJTuvn819M8mlv3tgZt/Tl4YyQTCw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:19:25.305232Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.02461","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:991f722a1bcecc0639562bc224c84430573ab384408dd95eb311e8dbb660c4ba","sha256:8144c58468da4c8136d51090b42f325d484f9362cd5cb7aea961b603f1c78226"],"state_sha256":"ed6fe36ffe397609fe6a25e51debf02342268eadf7c4f44f70dbc5484c772694"}