{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:ZGHMFVA5WN5POXM3S5MSBFNPGN","short_pith_number":"pith:ZGHMFVA5","schema_version":"1.0","canonical_sha256":"c98ec2d41db37af75d9b97592095af337cd5ac351dbbd4d1080fc39175231bff","source":{"kind":"arxiv","id":"2308.02768","version":1},"attestation_state":"computed","paper":{"title":"FGLQR: Factor Graph Accelerator of LQR Control for Autonomous Machines","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AR","authors_text":"Bo Yu, Qiang Liu, Shao-Shan Liu, Yuhui Hao","submitted_at":"2023-08-05T02:19:04Z","abstract_excerpt":"Factor graph represents the factorization of a probability distribution function and serves as an effective abstraction in various autonomous machine computing tasks. Control is one of the core applications in autonomous machine computing stacks. Among all control algorithms, Linear Quadratic Regulator (LQR) offers one of the best trade-offs between efficiency and accuracy. However, due to the inherent iterative process and extensive computation, it is a challenging task for the autonomous systems with real-time limits and energy constrained.\n  In this paper, we present FGLQR, an accelerator o"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2308.02768","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2023-08-05T02:19:04Z","cross_cats_sorted":[],"title_canon_sha256":"7d2854cfb47b41d0bb9da16a5faef0eadf5b52f58dddb27e313bdf28416e6666","abstract_canon_sha256":"fa9250f8fa64a8cffa6eb36310e597889cf51f93f64137339342cad72c8931c0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:38:07.151491Z","signature_b64":"liDLEHRqsIc2hykiATLtRYFN9CXqaktdKnn9TxWzvujlaePEa0YYhDkmNIsXkiZFU7YBY25qgfRemanLXfiTCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c98ec2d41db37af75d9b97592095af337cd5ac351dbbd4d1080fc39175231bff","last_reissued_at":"2026-07-05T06:38:07.150997Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:38:07.150997Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FGLQR: Factor Graph Accelerator of LQR Control for Autonomous Machines","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AR","authors_text":"Bo Yu, Qiang Liu, Shao-Shan Liu, Yuhui Hao","submitted_at":"2023-08-05T02:19:04Z","abstract_excerpt":"Factor graph represents the factorization of a probability distribution function and serves as an effective abstraction in various autonomous machine computing tasks. Control is one of the core applications in autonomous machine computing stacks. Among all control algorithms, Linear Quadratic Regulator (LQR) offers one of the best trade-offs between efficiency and accuracy. However, due to the inherent iterative process and extensive computation, it is a challenging task for the autonomous systems with real-time limits and energy constrained.\n  In this paper, we present FGLQR, an accelerator o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.02768","kind":"arxiv","version":1},"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/2308.02768/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2308.02768","created_at":"2026-07-05T06:38:07.151054+00:00"},{"alias_kind":"arxiv_version","alias_value":"2308.02768v1","created_at":"2026-07-05T06:38:07.151054+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.02768","created_at":"2026-07-05T06:38:07.151054+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZGHMFVA5WN5P","created_at":"2026-07-05T06:38:07.151054+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZGHMFVA5WN5POXM3","created_at":"2026-07-05T06:38:07.151054+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZGHMFVA5","created_at":"2026-07-05T06:38:07.151054+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ZGHMFVA5WN5POXM3S5MSBFNPGN","json":"https://pith.science/pith/ZGHMFVA5WN5POXM3S5MSBFNPGN.json","graph_json":"https://pith.science/api/pith-number/ZGHMFVA5WN5POXM3S5MSBFNPGN/graph.json","events_json":"https://pith.science/api/pith-number/ZGHMFVA5WN5POXM3S5MSBFNPGN/events.json","paper":"https://pith.science/paper/ZGHMFVA5"},"agent_actions":{"view_html":"https://pith.science/pith/ZGHMFVA5WN5POXM3S5MSBFNPGN","download_json":"https://pith.science/pith/ZGHMFVA5WN5POXM3S5MSBFNPGN.json","view_paper":"https://pith.science/paper/ZGHMFVA5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2308.02768&json=true","fetch_graph":"https://pith.science/api/pith-number/ZGHMFVA5WN5POXM3S5MSBFNPGN/graph.json","fetch_events":"https://pith.science/api/pith-number/ZGHMFVA5WN5POXM3S5MSBFNPGN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZGHMFVA5WN5POXM3S5MSBFNPGN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZGHMFVA5WN5POXM3S5MSBFNPGN/action/storage_attestation","attest_author":"https://pith.science/pith/ZGHMFVA5WN5POXM3S5MSBFNPGN/action/author_attestation","sign_citation":"https://pith.science/pith/ZGHMFVA5WN5POXM3S5MSBFNPGN/action/citation_signature","submit_replication":"https://pith.science/pith/ZGHMFVA5WN5POXM3S5MSBFNPGN/action/replication_record"}},"created_at":"2026-07-05T06:38:07.151054+00:00","updated_at":"2026-07-05T06:38:07.151054+00:00"}