{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:SSXMJVKW73NWZMVX4YL7YFKZXJ","short_pith_number":"pith:SSXMJVKW","schema_version":"1.0","canonical_sha256":"94aec4d556fedb6cb2b7e617fc1559ba663ecefe30d89d69c0ea481dd82d71fd","source":{"kind":"arxiv","id":"2504.11502","version":1},"attestation_state":"computed","paper":{"title":"Timing Analysis Agent: Autonomous Multi-Corner Multi-Mode (MCMM) Timing Debugging with Timing Debug Relation Graph","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.SE","authors_text":"Anirudh Dhurka, Chia-Tung Ho, Haoxing Ren, Jatin Nainani","submitted_at":"2025-04-15T04:14:36Z","abstract_excerpt":"Timing analysis is an essential and demanding verification method for Very Large Scale Integrated (VLSI) circuit design and optimization. In addition, it also serves as the cornerstone of the final sign-off, determining whether the chip is ready to be sent to the semiconductor foundry for fabrication. Recently, as the technology advance relentlessly, smaller metal pitches and the increasing number of devices have led to greater challenges and longer turn-around-time for experienced human designers to debug timing issues from the Multi-Corner Multi-Mode (MCMM) timing reports. As a result, an ef"},"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":"2504.11502","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2025-04-15T04:14:36Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"805e44b44e2b51d48b04335a897f1158f014ecde3e439675f9021c8b071159f7","abstract_canon_sha256":"f3946877c062c5f220954613c03e87243349627815f0b5901825610a8667488e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:49:36.198495Z","signature_b64":"1jooB65WddR6LNQynB/Ksk4j6e2kMYpVpSJD8XdYOs7FVASWeao4W5bDuMjXZZtQmmDDa+jtJoG2PxPsjnAICw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"94aec4d556fedb6cb2b7e617fc1559ba663ecefe30d89d69c0ea481dd82d71fd","last_reissued_at":"2026-07-05T10:49:36.198147Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:49:36.198147Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Timing Analysis Agent: Autonomous Multi-Corner Multi-Mode (MCMM) Timing Debugging with Timing Debug Relation Graph","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.SE","authors_text":"Anirudh Dhurka, Chia-Tung Ho, Haoxing Ren, Jatin Nainani","submitted_at":"2025-04-15T04:14:36Z","abstract_excerpt":"Timing analysis is an essential and demanding verification method for Very Large Scale Integrated (VLSI) circuit design and optimization. In addition, it also serves as the cornerstone of the final sign-off, determining whether the chip is ready to be sent to the semiconductor foundry for fabrication. Recently, as the technology advance relentlessly, smaller metal pitches and the increasing number of devices have led to greater challenges and longer turn-around-time for experienced human designers to debug timing issues from the Multi-Corner Multi-Mode (MCMM) timing reports. As a result, an ef"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.11502","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/2504.11502/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":"2504.11502","created_at":"2026-07-05T10:49:36.198202+00:00"},{"alias_kind":"arxiv_version","alias_value":"2504.11502v1","created_at":"2026-07-05T10:49:36.198202+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.11502","created_at":"2026-07-05T10:49:36.198202+00:00"},{"alias_kind":"pith_short_12","alias_value":"SSXMJVKW73NW","created_at":"2026-07-05T10:49:36.198202+00:00"},{"alias_kind":"pith_short_16","alias_value":"SSXMJVKW73NWZMVX","created_at":"2026-07-05T10:49:36.198202+00:00"},{"alias_kind":"pith_short_8","alias_value":"SSXMJVKW","created_at":"2026-07-05T10:49:36.198202+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2508.13257","citing_title":"ViTAD: Timing Violation-Aware Debugging of RTL Code using Large Language Models","ref_index":13,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SSXMJVKW73NWZMVX4YL7YFKZXJ","json":"https://pith.science/pith/SSXMJVKW73NWZMVX4YL7YFKZXJ.json","graph_json":"https://pith.science/api/pith-number/SSXMJVKW73NWZMVX4YL7YFKZXJ/graph.json","events_json":"https://pith.science/api/pith-number/SSXMJVKW73NWZMVX4YL7YFKZXJ/events.json","paper":"https://pith.science/paper/SSXMJVKW"},"agent_actions":{"view_html":"https://pith.science/pith/SSXMJVKW73NWZMVX4YL7YFKZXJ","download_json":"https://pith.science/pith/SSXMJVKW73NWZMVX4YL7YFKZXJ.json","view_paper":"https://pith.science/paper/SSXMJVKW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2504.11502&json=true","fetch_graph":"https://pith.science/api/pith-number/SSXMJVKW73NWZMVX4YL7YFKZXJ/graph.json","fetch_events":"https://pith.science/api/pith-number/SSXMJVKW73NWZMVX4YL7YFKZXJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SSXMJVKW73NWZMVX4YL7YFKZXJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SSXMJVKW73NWZMVX4YL7YFKZXJ/action/storage_attestation","attest_author":"https://pith.science/pith/SSXMJVKW73NWZMVX4YL7YFKZXJ/action/author_attestation","sign_citation":"https://pith.science/pith/SSXMJVKW73NWZMVX4YL7YFKZXJ/action/citation_signature","submit_replication":"https://pith.science/pith/SSXMJVKW73NWZMVX4YL7YFKZXJ/action/replication_record"}},"created_at":"2026-07-05T10:49:36.198202+00:00","updated_at":"2026-07-05T10:49:36.198202+00:00"}