{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:TTXTPDR7QKMX42EJ2RFKP4VTRC","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":"dd22715ca9357cbec2950234ea8632cc981b0e4e46b1e9fd4785a98c6b74f6be","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-04-27T07:13:33Z","title_canon_sha256":"b2a4f616bae25d74bf34ca57fb2a4b6947a831c400e5e0b374355ea21ba51166"},"schema_version":"1.0","source":{"id":"2604.24119","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.24119","created_at":"2026-06-11T01:09:36Z"},{"alias_kind":"arxiv_version","alias_value":"2604.24119v2","created_at":"2026-06-11T01:09:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.24119","created_at":"2026-06-11T01:09:36Z"},{"alias_kind":"pith_short_12","alias_value":"TTXTPDR7QKMX","created_at":"2026-06-11T01:09:36Z"},{"alias_kind":"pith_short_16","alias_value":"TTXTPDR7QKMX42EJ","created_at":"2026-06-11T01:09:36Z"},{"alias_kind":"pith_short_8","alias_value":"TTXTPDR7","created_at":"2026-06-11T01:09:36Z"}],"graph_snapshots":[{"event_id":"sha256:4b53b45c7d68c1c65c9909b3f907eb3bc2a1ddf959a997593eac64ec436868c5","target":"graph","created_at":"2026-06-11T01:09:36Z","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":4,"items":[{"attestation":"unclaimed","claim_id":"C1","kind":"strongest_claim","source":"verdict.strongest_claim","status":"machine_extracted","text":"On the OpenLane-V2 benchmark, TopoHR refreshes state-of-the-art performance with significant improvements. Notably, compared with previous best results, TopoHR achieves +3.8 in DET_l, +5.4 in TOP_ll on subset_A and +11.0 in DET_l, +7.9 in TOP_ll on subset_B, validating the effectiveness of the proposed components."},{"attestation":"unclaimed","claim_id":"C2","kind":"weakest_assumption","source":"verdict.weakest_assumption","status":"machine_extracted","text":"That the cyclic interaction between centerline detection and topology reasoning, enabled by the hierarchical point-to-instance features, is the primary driver of the reported benchmark gains rather than other unstated factors such as training details or dataset specifics."},{"attestation":"unclaimed","claim_id":"C3","kind":"one_line_summary","source":"verdict.one_line_summary","status":"machine_extracted","text":"TopoHR proposes a hierarchical centerline representation and topology reasoning module with point-to-instance relations and cyclic interactions, achieving new state-of-the-art results on the OpenLane-V2 benchmark for autonomous driving."},{"attestation":"unclaimed","claim_id":"C4","kind":"headline","source":"verdict.pith_extraction.headline","status":"machine_extracted","text":"Cyclic interaction between centerline detection and topology reasoning, driven by hierarchical point-to-instance features, improves road layout understanding in driving scenes."}],"snapshot_sha256":"cd28373c42543c79bff1476ebec772bc3f2a35cfea5d9292d3d71783f69f0e2c"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-21T07:38:38.138815Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"doi_compliance","ran_at":"2026-05-19T22:24:22.466179Z","status":"completed","version":"1.0.0"}],"endpoint":"/pith/2604.24119/integrity.json","findings":[],"snapshot_sha256":"7c4a7e82afbea55dc3b39f5de6605085b94fe6cf4088a7df0d4c30f012bc4222","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Topology reasoning is crucial for autonomous driving. Current methods primarily focus on instance-level learning for centerline detection, followed by a sequential module for topology reasoning that relies on simplified MLP layers. Moreover, they often neglect the importance of \\textit{point-to-instance} (P2I) relationships in topology reasoning. To address these limitations, we present TopoHR (Topological Hierarchical Representation), a novel end-to-end framework that establishes cyclic interaction between centerline detection and topology reasoning, allowing them to iteratively enhance each ","authors_text":"Bo Song, Erkang Cheng, Haibin Ling, Yifeng Bai, Zhirong Chen","cross_cats":[],"headline":"Cyclic interaction between centerline detection and topology reasoning, driven by hierarchical point-to-instance features, improves road layout understanding in driving scenes.","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-04-27T07:13:33Z","title":"TopoHR: Hierarchical Centerline Representation for Cyclic Topology Reasoning in Driving Scenes with Point-to-Instance Relations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.24119","kind":"arxiv","version":2},"verdict":{"created_at":"2026-05-08T04:32:58.989154Z","id":"c53fd2ce-2a91-48bd-9ed8-3b6fa9da9f79","model_set":{"reader":"grok-4.3"},"one_line_summary":"TopoHR proposes a hierarchical centerline representation and topology reasoning module with point-to-instance relations and cyclic interactions, achieving new state-of-the-art results on the OpenLane-V2 benchmark for autonomous driving.","pipeline_version":"pith-pipeline@v0.9.0","pith_extraction_headline":"Cyclic interaction between centerline detection and topology reasoning, driven by hierarchical point-to-instance features, improves road layout understanding in driving scenes.","strongest_claim":"On the OpenLane-V2 benchmark, TopoHR refreshes state-of-the-art performance with significant improvements. Notably, compared with previous best results, TopoHR achieves +3.8 in DET_l, +5.4 in TOP_ll on subset_A and +11.0 in DET_l, +7.9 in TOP_ll on subset_B, validating the effectiveness of the proposed components.","weakest_assumption":"That the cyclic interaction between centerline detection and topology reasoning, enabled by the hierarchical point-to-instance features, is the primary driver of the reported benchmark gains rather than other unstated factors such as training details or dataset specifics."}},"verdict_id":"c53fd2ce-2a91-48bd-9ed8-3b6fa9da9f79"}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:44d9b0d6b848145352090363393bb0a6a4d1792858fa857524137229f69132cf","target":"record","created_at":"2026-06-11T01:09:36Z","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":"dd22715ca9357cbec2950234ea8632cc981b0e4e46b1e9fd4785a98c6b74f6be","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-04-27T07:13:33Z","title_canon_sha256":"b2a4f616bae25d74bf34ca57fb2a4b6947a831c400e5e0b374355ea21ba51166"},"schema_version":"1.0","source":{"id":"2604.24119","kind":"arxiv","version":2}},"canonical_sha256":"9cef378e3f82997e6889d44aa7f2b388bdcf458ccfb720dca030c2e7cda248d8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9cef378e3f82997e6889d44aa7f2b388bdcf458ccfb720dca030c2e7cda248d8","first_computed_at":"2026-06-11T01:09:36.427623Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-11T01:09:36.427623Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LkGfp7vFENCPiXB9HOFQ4/SEpNdqUrtiwV6+SK1AEE9QeUEvQdfrN49BwR3Khv7AGcsfnMoI+jiQiqz20hVEBg==","signature_status":"signed_v1","signed_at":"2026-06-11T01:09:36.428924Z","signed_message":"canonical_sha256_bytes"},"source_id":"2604.24119","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:44d9b0d6b848145352090363393bb0a6a4d1792858fa857524137229f69132cf","sha256:4b53b45c7d68c1c65c9909b3f907eb3bc2a1ddf959a997593eac64ec436868c5"],"state_sha256":"1eb4adf6269e0a0c80d307641a009607de95d7efb715fd9ae56ac8df9b71d5e5"}