{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:BSC455Z43CY2G6PVBVZL4BQEWR","short_pith_number":"pith:BSC455Z4","schema_version":"1.0","canonical_sha256":"0c85cef73cd8b1a379f50d72be0604b4547842a46c5d960a2d907c6d662431fc","source":{"kind":"arxiv","id":"2606.08904","version":1},"attestation_state":"computed","paper":{"title":"Order Matters: Unveiling the Hidden Impact of Macro Placement Sequences via Proxy-Guided LLM Evolution","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Jianchu Xu, Jing Liu, Ruilin Wu, Shibing Mo","submitted_at":"2026-06-08T01:10:07Z","abstract_excerpt":"Macro placement is a fundamental step in modern chip physical design, playing a crucial role in determining the solution quality of high-dimensional combinatorial optimization problems. Despite recent advancements in machine learning for spatial coordinate determination, the temporal dimension of placement sequencing remains largely governed by static heuristics. In this work, we demonstrate that the placement sequence is not merely a preprocessing step but a decisive factor in optimization, where suboptimal early decisions trigger irreversible domino effects that constrain the solution space."},"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":"2606.08904","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-08T01:10:07Z","cross_cats_sorted":[],"title_canon_sha256":"14bf954f35b29adb3064f57445ac550ac0e8e44b863dfed07e609c1d6e8fe262","abstract_canon_sha256":"90d2944ba3ce8c318fa6a176507c9d509c9e5e0962f7de52c0f764af34b0d6ad"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-09T02:07:46.438097Z","signature_b64":"dwIoRwT4C+LOJ1DQx4moB4npFlw7z+yc7i1tE968ygMoB1ZX9K4ZVidljZEuf+evwnqO6DGKrY9P3vNgsCZqCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0c85cef73cd8b1a379f50d72be0604b4547842a46c5d960a2d907c6d662431fc","last_reissued_at":"2026-06-09T02:07:46.437294Z","signature_status":"signed_v1","first_computed_at":"2026-06-09T02:07:46.437294Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Order Matters: Unveiling the Hidden Impact of Macro Placement Sequences via Proxy-Guided LLM Evolution","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Jianchu Xu, Jing Liu, Ruilin Wu, Shibing Mo","submitted_at":"2026-06-08T01:10:07Z","abstract_excerpt":"Macro placement is a fundamental step in modern chip physical design, playing a crucial role in determining the solution quality of high-dimensional combinatorial optimization problems. Despite recent advancements in machine learning for spatial coordinate determination, the temporal dimension of placement sequencing remains largely governed by static heuristics. In this work, we demonstrate that the placement sequence is not merely a preprocessing step but a decisive factor in optimization, where suboptimal early decisions trigger irreversible domino effects that constrain the solution space."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.08904","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/2606.08904/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":"2606.08904","created_at":"2026-06-09T02:07:46.437430+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.08904v1","created_at":"2026-06-09T02:07:46.437430+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.08904","created_at":"2026-06-09T02:07:46.437430+00:00"},{"alias_kind":"pith_short_12","alias_value":"BSC455Z43CY2","created_at":"2026-06-09T02:07:46.437430+00:00"},{"alias_kind":"pith_short_16","alias_value":"BSC455Z43CY2G6PV","created_at":"2026-06-09T02:07:46.437430+00:00"},{"alias_kind":"pith_short_8","alias_value":"BSC455Z4","created_at":"2026-06-09T02:07:46.437430+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/BSC455Z43CY2G6PVBVZL4BQEWR","json":"https://pith.science/pith/BSC455Z43CY2G6PVBVZL4BQEWR.json","graph_json":"https://pith.science/api/pith-number/BSC455Z43CY2G6PVBVZL4BQEWR/graph.json","events_json":"https://pith.science/api/pith-number/BSC455Z43CY2G6PVBVZL4BQEWR/events.json","paper":"https://pith.science/paper/BSC455Z4"},"agent_actions":{"view_html":"https://pith.science/pith/BSC455Z43CY2G6PVBVZL4BQEWR","download_json":"https://pith.science/pith/BSC455Z43CY2G6PVBVZL4BQEWR.json","view_paper":"https://pith.science/paper/BSC455Z4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.08904&json=true","fetch_graph":"https://pith.science/api/pith-number/BSC455Z43CY2G6PVBVZL4BQEWR/graph.json","fetch_events":"https://pith.science/api/pith-number/BSC455Z43CY2G6PVBVZL4BQEWR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BSC455Z43CY2G6PVBVZL4BQEWR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BSC455Z43CY2G6PVBVZL4BQEWR/action/storage_attestation","attest_author":"https://pith.science/pith/BSC455Z43CY2G6PVBVZL4BQEWR/action/author_attestation","sign_citation":"https://pith.science/pith/BSC455Z43CY2G6PVBVZL4BQEWR/action/citation_signature","submit_replication":"https://pith.science/pith/BSC455Z43CY2G6PVBVZL4BQEWR/action/replication_record"}},"created_at":"2026-06-09T02:07:46.437430+00:00","updated_at":"2026-06-09T02:07:46.437430+00:00"}