{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:V2RDSZ3CKMB26FJN2ZYKTO3ZAR","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":"03896f9a1b1cf436f982c41acffbd2a2c5f876893cc5058d714e8f033578cde4","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-02-27T09:17:35Z","title_canon_sha256":"004a9d7088a4030481c65d2393c6e60cad8c1a03842a004f6e37631b2d60b8d6"},"schema_version":"1.0","source":{"id":"2302.13608","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.13608","created_at":"2026-07-05T07:11:54Z"},{"alias_kind":"arxiv_version","alias_value":"2302.13608v2","created_at":"2026-07-05T07:11:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.13608","created_at":"2026-07-05T07:11:54Z"},{"alias_kind":"pith_short_12","alias_value":"V2RDSZ3CKMB2","created_at":"2026-07-05T07:11:54Z"},{"alias_kind":"pith_short_16","alias_value":"V2RDSZ3CKMB26FJN","created_at":"2026-07-05T07:11:54Z"},{"alias_kind":"pith_short_8","alias_value":"V2RDSZ3C","created_at":"2026-07-05T07:11:54Z"}],"graph_snapshots":[{"event_id":"sha256:727ea3344f6c92d2577b0c70afefa328c726b1fc602a9410922b5b6638c4d60a","target":"graph","created_at":"2026-07-05T07:11:54Z","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/2302.13608/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Circuit representation learning is a promising research direction in the electronic design automation (EDA) field. With sufficient data for pre-training, the learned general yet effective representation can help to solve multiple downstream EDA tasks by fine-tuning it on a small set of task-related data. However, existing solutions only target combinational circuits, significantly limiting their applications. In this work, we propose DeepSeq, a novel representation learning framework for sequential netlists. Specifically, we introduce a dedicated graph neural network (GNN) with a customized pr","authors_text":"Min Li, Qiang Xu, Sadaf Khan, Zhengyuan Shi","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-02-27T09:17:35Z","title":"DeepSeq: Deep Sequential Circuit Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.13608","kind":"arxiv","version":2},"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":"sha256:1fa2cd172f4192b6a1c5beb678e2378c46c5054b6a34f9f38272ff168cc2810e","target":"record","created_at":"2026-07-05T07:11:54Z","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":"03896f9a1b1cf436f982c41acffbd2a2c5f876893cc5058d714e8f033578cde4","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-02-27T09:17:35Z","title_canon_sha256":"004a9d7088a4030481c65d2393c6e60cad8c1a03842a004f6e37631b2d60b8d6"},"schema_version":"1.0","source":{"id":"2302.13608","kind":"arxiv","version":2}},"canonical_sha256":"aea23967625303af152dd670a9bb7904657b9cf5c906917ec91994576e13ca00","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aea23967625303af152dd670a9bb7904657b9cf5c906917ec91994576e13ca00","first_computed_at":"2026-07-05T07:11:54.334710Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:11:54.334710Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EMlrdKRumr2vhi1wNfGqAGrIi6XaCe/cMg6II7unjbAYWPUH2N7Sxtt6mcReUNvL6vkrxX6813IBqILzGap+Aw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:11:54.335248Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.13608","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1fa2cd172f4192b6a1c5beb678e2378c46c5054b6a34f9f38272ff168cc2810e","sha256:727ea3344f6c92d2577b0c70afefa328c726b1fc602a9410922b5b6638c4d60a"],"state_sha256":"2708db661297ce691875cb77ad2d2a46a985f1f796783266179122817e318001"}