{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:MCCYYVHZA6CX3X3CFNA5UGUF5F","short_pith_number":"pith:MCCYYVHZ","schema_version":"1.0","canonical_sha256":"60858c54f907857ddf622b41da1a85e94d7d8265e3697ba3102874e6c87c7d0d","source":{"kind":"arxiv","id":"2607.21017","version":1},"attestation_state":"computed","paper":{"title":"TableVerse: A Large-scale Tabletop Dataset with Real-world Grounded Layouts for Generalizable Manipulation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Boyuan Wang, Xueyu Song, Xutao Xue, Yue Zhang, Yu Sun","submitted_at":"2026-07-23T08:02:53Z","abstract_excerpt":"The development of generalizable robotic manipulation policies is inherently bounded by the availability of large-scale, high-fidelity scene data. While recent automated synthesis methods attempt to bridge this gap via text-to-layout hallucination or simplified procedural generation, they frequently suffer from physical implausibility and fail to capture the complex, dense clutter of actual human environments. In this paper, we introduce TableVerse, a fully automated Real2Sim pipeline that shifts the paradigm from imaginative layout generation to deterministic reconstruction from unstructured,"},"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":"2607.21017","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-23T08:02:53Z","cross_cats_sorted":[],"title_canon_sha256":"ebf12e0bf16830de9a49e2dee89c977c2a75f797f00418493ebbfcfaa380581d","abstract_canon_sha256":"07c1557e2453edfdd221d3f8baf4982c043bef190d718799fe6d7ddde1ea8310"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-24T01:23:47.609021Z","signature_b64":"itZc0OndVwOAHGGk6eqy7Ex6Y2RsDw21wsgoRLxgKAcW9rQ6zGLR8dEl0gDeWGnvqeJFVhNCJ0EqXplpytMYCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"60858c54f907857ddf622b41da1a85e94d7d8265e3697ba3102874e6c87c7d0d","last_reissued_at":"2026-07-24T01:23:47.608165Z","signature_status":"signed_v1","first_computed_at":"2026-07-24T01:23:47.608165Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"TableVerse: A Large-scale Tabletop Dataset with Real-world Grounded Layouts for Generalizable Manipulation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Boyuan Wang, Xueyu Song, Xutao Xue, Yue Zhang, Yu Sun","submitted_at":"2026-07-23T08:02:53Z","abstract_excerpt":"The development of generalizable robotic manipulation policies is inherently bounded by the availability of large-scale, high-fidelity scene data. While recent automated synthesis methods attempt to bridge this gap via text-to-layout hallucination or simplified procedural generation, they frequently suffer from physical implausibility and fail to capture the complex, dense clutter of actual human environments. In this paper, we introduce TableVerse, a fully automated Real2Sim pipeline that shifts the paradigm from imaginative layout generation to deterministic reconstruction from unstructured,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.21017","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/2607.21017/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":"2607.21017","created_at":"2026-07-24T01:23:47.608614+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.21017v1","created_at":"2026-07-24T01:23:47.608614+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.21017","created_at":"2026-07-24T01:23:47.608614+00:00"},{"alias_kind":"pith_short_12","alias_value":"MCCYYVHZA6CX","created_at":"2026-07-24T01:23:47.608614+00:00"},{"alias_kind":"pith_short_16","alias_value":"MCCYYVHZA6CX3X3C","created_at":"2026-07-24T01:23:47.608614+00:00"},{"alias_kind":"pith_short_8","alias_value":"MCCYYVHZ","created_at":"2026-07-24T01:23:47.608614+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/MCCYYVHZA6CX3X3CFNA5UGUF5F","json":"https://pith.science/pith/MCCYYVHZA6CX3X3CFNA5UGUF5F.json","graph_json":"https://pith.science/api/pith-number/MCCYYVHZA6CX3X3CFNA5UGUF5F/graph.json","events_json":"https://pith.science/api/pith-number/MCCYYVHZA6CX3X3CFNA5UGUF5F/events.json","paper":"https://pith.science/paper/MCCYYVHZ"},"agent_actions":{"view_html":"https://pith.science/pith/MCCYYVHZA6CX3X3CFNA5UGUF5F","download_json":"https://pith.science/pith/MCCYYVHZA6CX3X3CFNA5UGUF5F.json","view_paper":"https://pith.science/paper/MCCYYVHZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.21017&json=true","fetch_graph":"https://pith.science/api/pith-number/MCCYYVHZA6CX3X3CFNA5UGUF5F/graph.json","fetch_events":"https://pith.science/api/pith-number/MCCYYVHZA6CX3X3CFNA5UGUF5F/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MCCYYVHZA6CX3X3CFNA5UGUF5F/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MCCYYVHZA6CX3X3CFNA5UGUF5F/action/storage_attestation","attest_author":"https://pith.science/pith/MCCYYVHZA6CX3X3CFNA5UGUF5F/action/author_attestation","sign_citation":"https://pith.science/pith/MCCYYVHZA6CX3X3CFNA5UGUF5F/action/citation_signature","submit_replication":"https://pith.science/pith/MCCYYVHZA6CX3X3CFNA5UGUF5F/action/replication_record"}},"created_at":"2026-07-24T01:23:47.608614+00:00","updated_at":"2026-07-24T01:23:47.608614+00:00"}