{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:F35G5SYV4X2ZCEPWUGJNUAULQI","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":"0bffbbd8cda4b910fab3bed22fa267262260c025700cc63e9498b21e5014f25d","cross_cats_sorted":["cs.AI","cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2026-08-05T16:09:12Z","title_canon_sha256":"a69fd17414583a3340e9c66bf8e129c62ff2b35a4975e8d5ca9e599ab4a65ec7"},"schema_version":"1.0","source":{"id":"2608.04999","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.04999","created_at":"2026-08-06T01:48:01Z"},{"alias_kind":"arxiv_version","alias_value":"2608.04999v1","created_at":"2026-08-06T01:48:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.04999","created_at":"2026-08-06T01:48:01Z"},{"alias_kind":"pith_short_12","alias_value":"F35G5SYV4X2Z","created_at":"2026-08-06T01:48:01Z"},{"alias_kind":"pith_short_16","alias_value":"F35G5SYV4X2ZCEPW","created_at":"2026-08-06T01:48:01Z"},{"alias_kind":"pith_short_8","alias_value":"F35G5SYV","created_at":"2026-08-06T01:48:01Z"}],"graph_snapshots":[{"event_id":"sha256:c841a02574ab9b8f592823d4731420db7470338fdc1a2e800651144d7dca901b","target":"graph","created_at":"2026-08-06T01:48:01Z","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/2608.04999/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Analog circuit design automation using reinforcement learning (RL) has emerged as a promising approach for reducing manual effort. However, many existing RL-based methods focus on single-objective optimization. Even methods designed for multi-objective (MO) problems often reduce multiple design specifications to a single scalar reward. This simplification limits the ability to capture the true Pareto trade-off among competing objectives and often leads to suboptimal designs. Moreover, requiring the model to be retrained from scratch whenever the desired MO specifications change remains a key l","authors_text":"Mohammed Ayman Habib, Morteza Fayazi, Osei Brempong, Vivan Poddar","cross_cats":["cs.AI","cs.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2026-08-05T16:09:12Z","title":"ORACLE: A Multi-Objective Reinforcement Learning-Based Analog Circuit Design Optimizer with Large Language Models-Guided Exploration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.04999","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":"sha256:77bf676155e1f3504da27ab5021c9593e27514e198b52d88ac9d237c9b3732d9","target":"record","created_at":"2026-08-06T01:48:01Z","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":"0bffbbd8cda4b910fab3bed22fa267262260c025700cc63e9498b21e5014f25d","cross_cats_sorted":["cs.AI","cs.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2026-08-05T16:09:12Z","title_canon_sha256":"a69fd17414583a3340e9c66bf8e129c62ff2b35a4975e8d5ca9e599ab4a65ec7"},"schema_version":"1.0","source":{"id":"2608.04999","kind":"arxiv","version":1}},"canonical_sha256":"2efa6ecb15e5f59111f6a192da028b8238c28c0264441c7b47dd59fb6ebb80a1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2efa6ecb15e5f59111f6a192da028b8238c28c0264441c7b47dd59fb6ebb80a1","first_computed_at":"2026-08-06T01:48:01.544275Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-06T01:48:01.544275Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0Z1tEMGzOKwdUKuBzjZqBr0pIAuht3sTyWpdRBPTN6I5f7kM07t3a0qgSKHghT0g08NKeAu7hpuRq7NUAxW3Dg==","signature_status":"signed_v1","signed_at":"2026-08-06T01:48:01.545734Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.04999","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:77bf676155e1f3504da27ab5021c9593e27514e198b52d88ac9d237c9b3732d9","sha256:c841a02574ab9b8f592823d4731420db7470338fdc1a2e800651144d7dca901b"],"state_sha256":"0cd804fe01d34c9e332589496a25c4008ec4741d476e8835f0fc9d5cefe46959"}