{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:F62SHFD2Q7UBKLZHAS7RK4VA4S","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":"e2362379450a84cbeef7e4bcc77296fd5f12e46f4a86ed924de8e4f88e17d7a0","cross_cats_sorted":["cs.AR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-29T20:11:47Z","title_canon_sha256":"4f6dbf083c58c4ddafeba2553b3a80009ed86cca82fbb90e0a5143f2e6e70e48"},"schema_version":"1.0","source":{"id":"2403.00103","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.00103","created_at":"2026-07-05T07:50:58Z"},{"alias_kind":"arxiv_version","alias_value":"2403.00103v1","created_at":"2026-07-05T07:50:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.00103","created_at":"2026-07-05T07:50:58Z"},{"alias_kind":"pith_short_12","alias_value":"F62SHFD2Q7UB","created_at":"2026-07-05T07:50:58Z"},{"alias_kind":"pith_short_16","alias_value":"F62SHFD2Q7UBKLZH","created_at":"2026-07-05T07:50:58Z"},{"alias_kind":"pith_short_8","alias_value":"F62SHFD2","created_at":"2026-07-05T07:50:58Z"}],"graph_snapshots":[{"event_id":"sha256:1a5fac2f1480c6c91feddbbc09cff57f2adb55ca458b14a6e8fcb6c6f5feec68","target":"graph","created_at":"2026-07-05T07:50:58Z","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/2403.00103/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"There is substantial interest in the use of machine learning (ML)-based techniques throughout the electronic computer-aided design (CAD) flow, particularly methods based on deep learning. However, while deep learning methods have achieved state-of-the-art performance in several applications, recent work has demonstrated that neural networks are generally vulnerable to small, carefully chosen perturbations of their input (e.g. a single pixel change in an image). In this work, we investigate robustness in the context of ML-based EDA tools -- particularly for congestion prediction. As far as we a","authors_text":"Bill Lin, Chester Holtz, Chung-Kuan Cheng, Yucheng Wang","cross_cats":["cs.AR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-29T20:11:47Z","title":"On Robustness and Generalization of ML-Based Congestion Predictors to Valid and Imperceptible Perturbations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.00103","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:d854f59cb20466da0b91c05d1e03a6b3be3e58c7b2685fa94caba5291b9829f1","target":"record","created_at":"2026-07-05T07:50:58Z","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":"e2362379450a84cbeef7e4bcc77296fd5f12e46f4a86ed924de8e4f88e17d7a0","cross_cats_sorted":["cs.AR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-29T20:11:47Z","title_canon_sha256":"4f6dbf083c58c4ddafeba2553b3a80009ed86cca82fbb90e0a5143f2e6e70e48"},"schema_version":"1.0","source":{"id":"2403.00103","kind":"arxiv","version":1}},"canonical_sha256":"2fb523947a87e8152f2704bf1572a0e4bb279dd3991a0b2d867cd9adb656a1ae","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2fb523947a87e8152f2704bf1572a0e4bb279dd3991a0b2d867cd9adb656a1ae","first_computed_at":"2026-07-05T07:50:58.556868Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:50:58.556868Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/SgiBI0Um5yo9Eos9Um9psjepavzeHIaD13/3yAqvW1CBt76BsWUzjljnpWUXSG/6hmKbMykDKUH7WRlUTzjDw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:50:58.557363Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.00103","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d854f59cb20466da0b91c05d1e03a6b3be3e58c7b2685fa94caba5291b9829f1","sha256:1a5fac2f1480c6c91feddbbc09cff57f2adb55ca458b14a6e8fcb6c6f5feec68"],"state_sha256":"aab4f7e7b800b6e93a65743c08fe1b00099358f3e82deedffbf90484e1dcb086"}