{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:5PYCNDQMLRL6QOOHSQLLF4NS65","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":"9411d3e3ecce892e918cec69eab9c37edce206680de028acbc6c6887f0fa69e9","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-10T04:01:21Z","title_canon_sha256":"3ac40ff98c124460e8560eed4ecfce9ab56d392801b7d158efbc79ab16beefff"},"schema_version":"1.0","source":{"id":"2412.07167","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.07167","created_at":"2026-07-05T09:47:05Z"},{"alias_kind":"arxiv_version","alias_value":"2412.07167v1","created_at":"2026-07-05T09:47:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.07167","created_at":"2026-07-05T09:47:05Z"},{"alias_kind":"pith_short_12","alias_value":"5PYCNDQMLRL6","created_at":"2026-07-05T09:47:05Z"},{"alias_kind":"pith_short_16","alias_value":"5PYCNDQMLRL6QOOH","created_at":"2026-07-05T09:47:05Z"},{"alias_kind":"pith_short_8","alias_value":"5PYCNDQM","created_at":"2026-07-05T09:47:05Z"}],"graph_snapshots":[{"event_id":"sha256:fd7892971ec2843d56d5bb51ea2e1e7e084f67e4f93ab6a7fa37aea086c0a59d","target":"graph","created_at":"2026-07-05T09:47:05Z","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/2412.07167/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In modern chip design, placement aims at placing millions of circuit modules, which is an essential step that significantly influences power, performance, and area (PPA) metrics. Recently, reinforcement learning (RL) has emerged as a promising technique for improving placement quality, especially macro placement. However, current RL-based placement methods suffer from long training times, low generalization ability, and inability to guarantee PPA results. A key issue lies in the problem formulation, i.e., using RL to place from scratch, which results in limits useful information and inaccurate","authors_text":"Chao Qian, Ke Xue, Ruo-Tong Chen, Shixiong Kai, Siyuan Xu, Xi Lin, Yunqi Shi","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-10T04:01:21Z","title":"Reinforcement Learning Policy as Macro Regulator Rather than Macro Placer"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.07167","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":"sha256:702a4144e3cbac0e236624328443d84392bc542524ce1336774794a71a3cae3d","target":"record","created_at":"2026-07-05T09:47:05Z","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":"9411d3e3ecce892e918cec69eab9c37edce206680de028acbc6c6887f0fa69e9","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-12-10T04:01:21Z","title_canon_sha256":"3ac40ff98c124460e8560eed4ecfce9ab56d392801b7d158efbc79ab16beefff"},"schema_version":"1.0","source":{"id":"2412.07167","kind":"arxiv","version":1}},"canonical_sha256":"ebf0268e0c5c57e839c79416b2f1b2f754fd4e02b5fc8314f2ed37fc2dbfa36f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ebf0268e0c5c57e839c79416b2f1b2f754fd4e02b5fc8314f2ed37fc2dbfa36f","first_computed_at":"2026-07-05T09:47:05.005390Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:47:05.005390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kYSWBx4dVQt3/8OL2WYwGe0UiG1hXjxnCkMv0PbhKVyes7in+neSW0XUjgc3udryJR1fBDCQXuswZYFg54VGCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:47:05.005893Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.07167","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:702a4144e3cbac0e236624328443d84392bc542524ce1336774794a71a3cae3d","sha256:fd7892971ec2843d56d5bb51ea2e1e7e084f67e4f93ab6a7fa37aea086c0a59d"],"state_sha256":"fbf19fba8f26a8a1d7bd96f3b4a59092fd2d97d6a6a13d8fc46377449d2b0072"}