{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:U5QVZC4BPSPRZT7LAQW7KCDQDD","short_pith_number":"pith:U5QVZC4B","schema_version":"1.0","canonical_sha256":"a7615c8b817c9f1ccfeb042df5087018e463d994391fb5270a48862d760bfcae","source":{"kind":"arxiv","id":"2605.18094","version":1},"attestation_state":"computed","paper":{"title":"Learning to Solve Compositional Geometry Routing Problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Guillaume Adrien Sartoretti, Jianan Zhou, Jiaqi Cheng, Jie Zhang, Mingfeng Fan, Yifeng Zhang","submitted_at":"2026-05-18T09:10:15Z","abstract_excerpt":"We study the Compositional Geometry Routing Problem (CGRP), a unified superclass of traditional routing problems that covers point-only, line-only, area-only, and arbitrary hybrid task geometries, providing a broad abstraction for real-world routing scenarios. Beyond standard point-based routing, CGRP with non-point tasks can be inherently asymmetric, tightly coupled travel routes with the intrinsic path, and enlarges the action space with numerous feasible yet often irrelevant options, thereby posing significant challenges for both representation learning and decision-making. To address these"},"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":"2605.18094","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-18T09:10:15Z","cross_cats_sorted":[],"title_canon_sha256":"4d6195be16004e398af3744151fe3118bed809deccd101123660e761493e3a04","abstract_canon_sha256":"54e1b7ef08e40941267784a42d02a6bac6f725b8e4dfc67aa19a7afecf2a71ab"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:05:15.648283Z","signature_b64":"TCV0x2dsaLdNGfzbKYQsMrzxVi6W97yfDK4KpxVg0m42mE5o/u7sscbUHVrFh2IS0Pp586cmiP+VKM/aoORKAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a7615c8b817c9f1ccfeb042df5087018e463d994391fb5270a48862d760bfcae","last_reissued_at":"2026-05-20T00:05:15.647570Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:05:15.647570Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning to Solve Compositional Geometry Routing Problems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Guillaume Adrien Sartoretti, Jianan Zhou, Jiaqi Cheng, Jie Zhang, Mingfeng Fan, Yifeng Zhang","submitted_at":"2026-05-18T09:10:15Z","abstract_excerpt":"We study the Compositional Geometry Routing Problem (CGRP), a unified superclass of traditional routing problems that covers point-only, line-only, area-only, and arbitrary hybrid task geometries, providing a broad abstraction for real-world routing scenarios. Beyond standard point-based routing, CGRP with non-point tasks can be inherently asymmetric, tightly coupled travel routes with the intrinsic path, and enlarges the action space with numerous feasible yet often irrelevant options, thereby posing significant challenges for both representation learning and decision-making. To address these"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.18094","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/2605.18094/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"claim_evidence","ran_at":"2026-05-19T23:41:59.196693Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T23:33:35.435643Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"99fe537fd5a4f95d521e916b39b6428fafdcb9a825ec4db2f62656da215cb94f"},"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":"2605.18094","created_at":"2026-05-20T00:05:15.647689+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.18094v1","created_at":"2026-05-20T00:05:15.647689+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.18094","created_at":"2026-05-20T00:05:15.647689+00:00"},{"alias_kind":"pith_short_12","alias_value":"U5QVZC4BPSPR","created_at":"2026-05-20T00:05:15.647689+00:00"},{"alias_kind":"pith_short_16","alias_value":"U5QVZC4BPSPRZT7L","created_at":"2026-05-20T00:05:15.647689+00:00"},{"alias_kind":"pith_short_8","alias_value":"U5QVZC4B","created_at":"2026-05-20T00:05:15.647689+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/U5QVZC4BPSPRZT7LAQW7KCDQDD","json":"https://pith.science/pith/U5QVZC4BPSPRZT7LAQW7KCDQDD.json","graph_json":"https://pith.science/api/pith-number/U5QVZC4BPSPRZT7LAQW7KCDQDD/graph.json","events_json":"https://pith.science/api/pith-number/U5QVZC4BPSPRZT7LAQW7KCDQDD/events.json","paper":"https://pith.science/paper/U5QVZC4B"},"agent_actions":{"view_html":"https://pith.science/pith/U5QVZC4BPSPRZT7LAQW7KCDQDD","download_json":"https://pith.science/pith/U5QVZC4BPSPRZT7LAQW7KCDQDD.json","view_paper":"https://pith.science/paper/U5QVZC4B","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.18094&json=true","fetch_graph":"https://pith.science/api/pith-number/U5QVZC4BPSPRZT7LAQW7KCDQDD/graph.json","fetch_events":"https://pith.science/api/pith-number/U5QVZC4BPSPRZT7LAQW7KCDQDD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/U5QVZC4BPSPRZT7LAQW7KCDQDD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/U5QVZC4BPSPRZT7LAQW7KCDQDD/action/storage_attestation","attest_author":"https://pith.science/pith/U5QVZC4BPSPRZT7LAQW7KCDQDD/action/author_attestation","sign_citation":"https://pith.science/pith/U5QVZC4BPSPRZT7LAQW7KCDQDD/action/citation_signature","submit_replication":"https://pith.science/pith/U5QVZC4BPSPRZT7LAQW7KCDQDD/action/replication_record"}},"created_at":"2026-05-20T00:05:15.647689+00:00","updated_at":"2026-05-20T00:05:15.647689+00:00"}