{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:FB5T6GAPSQFEQWWUUF6IHWIO4K","short_pith_number":"pith:FB5T6GAP","canonical_record":{"source":{"id":"2411.14296","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-21T16:42:41Z","cross_cats_sorted":[],"title_canon_sha256":"83cbfe2d0c6135c804f614f7a9798378ae502de8d719ba4314d23cd98d0dd6e1","abstract_canon_sha256":"4b8aef6cef250871d55984a87f69b252579ea30b604790149e30cd2fc5507223"},"schema_version":"1.0"},"canonical_sha256":"287b3f180f940a485ad4a17c83d90ee290134cc1749a785488c3172b41e8a7e3","source":{"kind":"arxiv","id":"2411.14296","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.14296","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"arxiv_version","alias_value":"2411.14296v1","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.14296","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"pith_short_12","alias_value":"FB5T6GAPSQFE","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"pith_short_16","alias_value":"FB5T6GAPSQFEQWWU","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"pith_short_8","alias_value":"FB5T6GAP","created_at":"2026-07-05T09:38:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:FB5T6GAPSQFEQWWUUF6IHWIO4K","target":"record","payload":{"canonical_record":{"source":{"id":"2411.14296","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-21T16:42:41Z","cross_cats_sorted":[],"title_canon_sha256":"83cbfe2d0c6135c804f614f7a9798378ae502de8d719ba4314d23cd98d0dd6e1","abstract_canon_sha256":"4b8aef6cef250871d55984a87f69b252579ea30b604790149e30cd2fc5507223"},"schema_version":"1.0"},"canonical_sha256":"287b3f180f940a485ad4a17c83d90ee290134cc1749a785488c3172b41e8a7e3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:38:44.821351Z","signature_b64":"8iqGur+43UyH0vG2iQYWnx73tg9MdH+5EqlgFdVq5J7BpTszRgOmO0Ig1ly5fNVfh2eh/4hjzZRscrPbRlDwDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"287b3f180f940a485ad4a17c83d90ee290134cc1749a785488c3172b41e8a7e3","last_reissued_at":"2026-07-05T09:38:44.820881Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:38:44.820881Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.14296","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:38:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1yrbcuIWROR4ImFFNkhRrLbR3SmzzzHXOdWC3JE5iRAE3Aek2WMxjvu6krEWPspfqIt+PQ+t+Q3+b9ZuK2WwBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T18:18:30.246812Z"},"content_sha256":"e7b6785a36b786f6d098e248ecdf46e6183c5a07ccb978b22e04a41edad3bdb9","schema_version":"1.0","event_id":"sha256:e7b6785a36b786f6d098e248ecdf46e6183c5a07ccb978b22e04a41edad3bdb9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:FB5T6GAPSQFEQWWUUF6IHWIO4K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving Routability Prediction via NAS Using a Smooth One-shot Augmented Predictor","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Arjun Sridhar, Chen-Chia Chang, Junyao Zhang, Yiran Chen","submitted_at":"2024-11-21T16:42:41Z","abstract_excerpt":"Routability optimization in modern EDA tools has benefited greatly from using machine learning (ML) models. Constructing and optimizing the performance of ML models continues to be a challenge. Neural Architecture Search (NAS) serves as a tool to aid in the construction and improvement of these models. Traditional NAS techniques struggle to perform well on routability prediction as a result of two primary factors. First, the separation between the training objective and the search objective adds noise to the NAS process. Secondly, the increased variance of the search objective further complica"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.14296","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/2411.14296/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:38:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nXWEsl5E5TTdUmk7fFFC7L3BOkAj0EmoSSdnVl3nDrquZVjVOgRd3vISU3TvNdK6LRniF1hDLdhFuyp7n2EVBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T18:18:30.247559Z"},"content_sha256":"632a8013eb2182392b324cd34ac4ad990bd89c7ae0bf10fa21a2a86a08a8d4bc","schema_version":"1.0","event_id":"sha256:632a8013eb2182392b324cd34ac4ad990bd89c7ae0bf10fa21a2a86a08a8d4bc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FB5T6GAPSQFEQWWUUF6IHWIO4K/bundle.json","state_url":"https://pith.science/pith/FB5T6GAPSQFEQWWUUF6IHWIO4K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FB5T6GAPSQFEQWWUUF6IHWIO4K/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-31T18:18:30Z","links":{"resolver":"https://pith.science/pith/FB5T6GAPSQFEQWWUUF6IHWIO4K","bundle":"https://pith.science/pith/FB5T6GAPSQFEQWWUUF6IHWIO4K/bundle.json","state":"https://pith.science/pith/FB5T6GAPSQFEQWWUUF6IHWIO4K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FB5T6GAPSQFEQWWUUF6IHWIO4K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:FB5T6GAPSQFEQWWUUF6IHWIO4K","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":"4b8aef6cef250871d55984a87f69b252579ea30b604790149e30cd2fc5507223","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-21T16:42:41Z","title_canon_sha256":"83cbfe2d0c6135c804f614f7a9798378ae502de8d719ba4314d23cd98d0dd6e1"},"schema_version":"1.0","source":{"id":"2411.14296","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.14296","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"arxiv_version","alias_value":"2411.14296v1","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.14296","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"pith_short_12","alias_value":"FB5T6GAPSQFE","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"pith_short_16","alias_value":"FB5T6GAPSQFEQWWU","created_at":"2026-07-05T09:38:44Z"},{"alias_kind":"pith_short_8","alias_value":"FB5T6GAP","created_at":"2026-07-05T09:38:44Z"}],"graph_snapshots":[{"event_id":"sha256:632a8013eb2182392b324cd34ac4ad990bd89c7ae0bf10fa21a2a86a08a8d4bc","target":"graph","created_at":"2026-07-05T09:38:44Z","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/2411.14296/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Routability optimization in modern EDA tools has benefited greatly from using machine learning (ML) models. Constructing and optimizing the performance of ML models continues to be a challenge. Neural Architecture Search (NAS) serves as a tool to aid in the construction and improvement of these models. Traditional NAS techniques struggle to perform well on routability prediction as a result of two primary factors. First, the separation between the training objective and the search objective adds noise to the NAS process. Secondly, the increased variance of the search objective further complica","authors_text":"Arjun Sridhar, Chen-Chia Chang, Junyao Zhang, Yiran Chen","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-21T16:42:41Z","title":"Improving Routability Prediction via NAS Using a Smooth One-shot Augmented Predictor"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.14296","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:e7b6785a36b786f6d098e248ecdf46e6183c5a07ccb978b22e04a41edad3bdb9","target":"record","created_at":"2026-07-05T09:38:44Z","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":"4b8aef6cef250871d55984a87f69b252579ea30b604790149e30cd2fc5507223","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-21T16:42:41Z","title_canon_sha256":"83cbfe2d0c6135c804f614f7a9798378ae502de8d719ba4314d23cd98d0dd6e1"},"schema_version":"1.0","source":{"id":"2411.14296","kind":"arxiv","version":1}},"canonical_sha256":"287b3f180f940a485ad4a17c83d90ee290134cc1749a785488c3172b41e8a7e3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"287b3f180f940a485ad4a17c83d90ee290134cc1749a785488c3172b41e8a7e3","first_computed_at":"2026-07-05T09:38:44.820881Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:38:44.820881Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8iqGur+43UyH0vG2iQYWnx73tg9MdH+5EqlgFdVq5J7BpTszRgOmO0Ig1ly5fNVfh2eh/4hjzZRscrPbRlDwDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:38:44.821351Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.14296","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e7b6785a36b786f6d098e248ecdf46e6183c5a07ccb978b22e04a41edad3bdb9","sha256:632a8013eb2182392b324cd34ac4ad990bd89c7ae0bf10fa21a2a86a08a8d4bc"],"state_sha256":"b3065fefef37bf39041302797099c04a368beab80773436690d81a6b7317c6c9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s+PuRYQvcmMWnEkjJLp93hJRK4urfWr+31ijhJa1UhKjtBu/KeOSatgVmHlmGCexjQE0v3DSIJRewpP3a34cBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T18:18:30.252385Z","bundle_sha256":"7c77f06ed74475555c0008d227f55a53c9b2bfb1266b3881c94dc478c2945f53"}}