{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:E2MF3PIZMCEYF2VZIA5DMAEQGK","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":"67436a9f29f2c2a370002524d80e937b3a4eab5b37adfad1889c346abdbe25e8","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-03-23T07:18:02Z","title_canon_sha256":"5d09a394738b65a3c83d3273bb4f40962cfd2db855af79473aecb81a10f21616"},"schema_version":"1.0","source":{"id":"2605.20189","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.20189","created_at":"2026-05-21T00:04:20Z"},{"alias_kind":"arxiv_version","alias_value":"2605.20189v1","created_at":"2026-05-21T00:04:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.20189","created_at":"2026-05-21T00:04:20Z"},{"alias_kind":"pith_short_12","alias_value":"E2MF3PIZMCEY","created_at":"2026-05-21T00:04:20Z"},{"alias_kind":"pith_short_16","alias_value":"E2MF3PIZMCEYF2VZ","created_at":"2026-05-21T00:04:20Z"},{"alias_kind":"pith_short_8","alias_value":"E2MF3PIZ","created_at":"2026-05-21T00:04:20Z"}],"graph_snapshots":[{"event_id":"sha256:63f7f1a2eb53dc669ca69ebe219bbb9ecfca00df0473f83a1f5086144ce3837e","target":"graph","created_at":"2026-05-21T00:04:20Z","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/2605.20189/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite the remarkable success of large language models (LLMs), they still face bottlenecks while deploying in dynamic, real-world settings with primary challenges being concept drift and the high cost of gradient-based adaptation. Traditional fine-tuning (FT) struggles to adapt to non-stationary data streams without resulting in catastrophic for getting or requiring extensive manual data curation. To address these limitations within the streaming and continual learning paradigm, we propose the Self-Optimizing Lifelong Autonomous Reasoner (SOLAR) which is an open-ended autonomous agent that le","authors_text":"Dianbo Liu, Nitin Vetcha","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-03-23T07:18:02Z","title":"SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.20189","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":"sha256:792250e1b841b623f676cb2ad0b4ff3a299c489432424bc4424c2656cee7e77e","target":"record","created_at":"2026-05-21T00:04:20Z","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":"67436a9f29f2c2a370002524d80e937b3a4eab5b37adfad1889c346abdbe25e8","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-03-23T07:18:02Z","title_canon_sha256":"5d09a394738b65a3c83d3273bb4f40962cfd2db855af79473aecb81a10f21616"},"schema_version":"1.0","source":{"id":"2605.20189","kind":"arxiv","version":1}},"canonical_sha256":"26985dbd19608982eab9403a360090329becc53fb572eb850fc5ec3776b740ba","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"26985dbd19608982eab9403a360090329becc53fb572eb850fc5ec3776b740ba","first_computed_at":"2026-05-21T00:04:20.332628Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-21T00:04:20.332628Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"suL4PsnnpOUOokXZT8h2oXNYitBsV/NfCPaalts8bKrlRWZLs1aceYsXxAswmp+knhj/DQxvj5Vr7tTb3CY0Cw==","signature_status":"signed_v1","signed_at":"2026-05-21T00:04:20.333242Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.20189","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:792250e1b841b623f676cb2ad0b4ff3a299c489432424bc4424c2656cee7e77e","sha256:63f7f1a2eb53dc669ca69ebe219bbb9ecfca00df0473f83a1f5086144ce3837e"],"state_sha256":"4c46264dd73d65567427d1a9b949fb22763d9519638f68d5c0efb19168ebd1f1"}