{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:JVIWLK6YRBILXVGCUOD3OW7HNI","short_pith_number":"pith:JVIWLK6Y","schema_version":"1.0","canonical_sha256":"4d5165abd88850bbd4c2a387b75be76a3948361bc9d10252a8db4d7aeb39eedf","source":{"kind":"arxiv","id":"2606.10431","version":1},"attestation_state":"computed","paper":{"title":"Vision-Assisted Foundation Model for Solving Multi-Task Vehicle Routing Problems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Shuangchun Gui, Wen Song, Yew-Soon Ong, Zhiguang Cao","submitted_at":"2026-06-09T05:15:25Z","abstract_excerpt":"Multi-task vehicle routing problems play a critical role in enhancing efficiency across various industries and service sectors. These problems consist of multiple variants that optimize routing costs while meeting diverse customer constraints. Existing multi-task VRP solvers solely utilize a graph-based modality, limiting their ability to address variants with multiple constraints. As a format to represent complex semantics, vision modality shows great potential for encoding diverse VRP constraints. This motivates us to learn patch-level semantics from the vision images, and then integrate the"},"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":"2606.10431","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-09T05:15:25Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"47e20a5ba2d313ddd8d4fa70b95d0166ef5dfd16492b4ca5b16e268964c9e037","abstract_canon_sha256":"4862c725df90e5df9088e61f1470570b0d520618006aa6cac0fe80d819a86d02"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-10T01:10:18.587462Z","signature_b64":"WOwDaquDH5MhXtAryfMurFzhVz+uwkXGNN0GtgtHaXcWQw+UqkYOgQMVkJbmeIpkM7UxhOdDwKSpF0/E9owHCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4d5165abd88850bbd4c2a387b75be76a3948361bc9d10252a8db4d7aeb39eedf","last_reissued_at":"2026-06-10T01:10:18.586509Z","signature_status":"signed_v1","first_computed_at":"2026-06-10T01:10:18.586509Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Vision-Assisted Foundation Model for Solving Multi-Task Vehicle Routing Problems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Shuangchun Gui, Wen Song, Yew-Soon Ong, Zhiguang Cao","submitted_at":"2026-06-09T05:15:25Z","abstract_excerpt":"Multi-task vehicle routing problems play a critical role in enhancing efficiency across various industries and service sectors. These problems consist of multiple variants that optimize routing costs while meeting diverse customer constraints. Existing multi-task VRP solvers solely utilize a graph-based modality, limiting their ability to address variants with multiple constraints. As a format to represent complex semantics, vision modality shows great potential for encoding diverse VRP constraints. This motivates us to learn patch-level semantics from the vision images, and then integrate the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.10431","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/2606.10431/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":"2606.10431","created_at":"2026-06-10T01:10:18.586687+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.10431v1","created_at":"2026-06-10T01:10:18.586687+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.10431","created_at":"2026-06-10T01:10:18.586687+00:00"},{"alias_kind":"pith_short_12","alias_value":"JVIWLK6YRBIL","created_at":"2026-06-10T01:10:18.586687+00:00"},{"alias_kind":"pith_short_16","alias_value":"JVIWLK6YRBILXVGC","created_at":"2026-06-10T01:10:18.586687+00:00"},{"alias_kind":"pith_short_8","alias_value":"JVIWLK6Y","created_at":"2026-06-10T01:10:18.586687+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/JVIWLK6YRBILXVGCUOD3OW7HNI","json":"https://pith.science/pith/JVIWLK6YRBILXVGCUOD3OW7HNI.json","graph_json":"https://pith.science/api/pith-number/JVIWLK6YRBILXVGCUOD3OW7HNI/graph.json","events_json":"https://pith.science/api/pith-number/JVIWLK6YRBILXVGCUOD3OW7HNI/events.json","paper":"https://pith.science/paper/JVIWLK6Y"},"agent_actions":{"view_html":"https://pith.science/pith/JVIWLK6YRBILXVGCUOD3OW7HNI","download_json":"https://pith.science/pith/JVIWLK6YRBILXVGCUOD3OW7HNI.json","view_paper":"https://pith.science/paper/JVIWLK6Y","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.10431&json=true","fetch_graph":"https://pith.science/api/pith-number/JVIWLK6YRBILXVGCUOD3OW7HNI/graph.json","fetch_events":"https://pith.science/api/pith-number/JVIWLK6YRBILXVGCUOD3OW7HNI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JVIWLK6YRBILXVGCUOD3OW7HNI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JVIWLK6YRBILXVGCUOD3OW7HNI/action/storage_attestation","attest_author":"https://pith.science/pith/JVIWLK6YRBILXVGCUOD3OW7HNI/action/author_attestation","sign_citation":"https://pith.science/pith/JVIWLK6YRBILXVGCUOD3OW7HNI/action/citation_signature","submit_replication":"https://pith.science/pith/JVIWLK6YRBILXVGCUOD3OW7HNI/action/replication_record"}},"created_at":"2026-06-10T01:10:18.586687+00:00","updated_at":"2026-06-10T01:10:18.586687+00:00"}