{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:AU56S2NPZ3B4BCNZM2RXULWHOQ","short_pith_number":"pith:AU56S2NP","schema_version":"1.0","canonical_sha256":"053be969afcec3c089b966a37a2ec77410d32b1557710b6fb7b5a9d2ee196718","source":{"kind":"arxiv","id":"2607.14728","version":1},"attestation_state":"computed","paper":{"title":"VQ-Touch: A Data-Efficient Tactile Generation Framework Across Sensors and Scenarios","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Di Wu, Jianing Zeng, Jie Hao, Kailin Lyu, Lin Shu, Long Xiao","submitted_at":"2026-07-16T08:53:41Z","abstract_excerpt":"Tactile image generation significantly reduces the dependency on expensive and wear-prone sensors by synthesizing high-fidelity tactile data, offering an efficient solution for tactile information acquisition in robotic perception and human-machine interaction systems. However, existing methods depend on large-scale, diverse datasets from specific sensors and lack efficient data utilization and robust generalization capabilities, struggling in vision-limited environments. To address this, we introduce VQ-Touch, a tactile generation framework that supports both cross-sensor and multi-scenario a"},"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":"2607.14728","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-07-16T08:53:41Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"f593b1132e43dda415a84c36e61f2b73e746bd73ae2ba35af265edb19c1d6aa4","abstract_canon_sha256":"2bc17df1b005efffc3da4e45fe1cdb1a97ede1df9ee41eb9adb8a5bd16d7bde7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-17T01:21:28.009031Z","signature_b64":"asGSDlV2hOOUawfce3QD3/Kt3OLRe/Bwh/5+tSEPN0YhbwKIfyNyxFX57YRF6iZnnIVtantGIuZhknlxTl1pBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"053be969afcec3c089b966a37a2ec77410d32b1557710b6fb7b5a9d2ee196718","last_reissued_at":"2026-07-17T01:21:28.008160Z","signature_status":"signed_v1","first_computed_at":"2026-07-17T01:21:28.008160Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"VQ-Touch: A Data-Efficient Tactile Generation Framework Across Sensors and Scenarios","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Di Wu, Jianing Zeng, Jie Hao, Kailin Lyu, Lin Shu, Long Xiao","submitted_at":"2026-07-16T08:53:41Z","abstract_excerpt":"Tactile image generation significantly reduces the dependency on expensive and wear-prone sensors by synthesizing high-fidelity tactile data, offering an efficient solution for tactile information acquisition in robotic perception and human-machine interaction systems. However, existing methods depend on large-scale, diverse datasets from specific sensors and lack efficient data utilization and robust generalization capabilities, struggling in vision-limited environments. To address this, we introduce VQ-Touch, a tactile generation framework that supports both cross-sensor and multi-scenario a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.14728","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/2607.14728/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":"2607.14728","created_at":"2026-07-17T01:21:28.008586+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.14728v1","created_at":"2026-07-17T01:21:28.008586+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.14728","created_at":"2026-07-17T01:21:28.008586+00:00"},{"alias_kind":"pith_short_12","alias_value":"AU56S2NPZ3B4","created_at":"2026-07-17T01:21:28.008586+00:00"},{"alias_kind":"pith_short_16","alias_value":"AU56S2NPZ3B4BCNZ","created_at":"2026-07-17T01:21:28.008586+00:00"},{"alias_kind":"pith_short_8","alias_value":"AU56S2NP","created_at":"2026-07-17T01:21:28.008586+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/AU56S2NPZ3B4BCNZM2RXULWHOQ","json":"https://pith.science/pith/AU56S2NPZ3B4BCNZM2RXULWHOQ.json","graph_json":"https://pith.science/api/pith-number/AU56S2NPZ3B4BCNZM2RXULWHOQ/graph.json","events_json":"https://pith.science/api/pith-number/AU56S2NPZ3B4BCNZM2RXULWHOQ/events.json","paper":"https://pith.science/paper/AU56S2NP"},"agent_actions":{"view_html":"https://pith.science/pith/AU56S2NPZ3B4BCNZM2RXULWHOQ","download_json":"https://pith.science/pith/AU56S2NPZ3B4BCNZM2RXULWHOQ.json","view_paper":"https://pith.science/paper/AU56S2NP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.14728&json=true","fetch_graph":"https://pith.science/api/pith-number/AU56S2NPZ3B4BCNZM2RXULWHOQ/graph.json","fetch_events":"https://pith.science/api/pith-number/AU56S2NPZ3B4BCNZM2RXULWHOQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AU56S2NPZ3B4BCNZM2RXULWHOQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AU56S2NPZ3B4BCNZM2RXULWHOQ/action/storage_attestation","attest_author":"https://pith.science/pith/AU56S2NPZ3B4BCNZM2RXULWHOQ/action/author_attestation","sign_citation":"https://pith.science/pith/AU56S2NPZ3B4BCNZM2RXULWHOQ/action/citation_signature","submit_replication":"https://pith.science/pith/AU56S2NPZ3B4BCNZM2RXULWHOQ/action/replication_record"}},"created_at":"2026-07-17T01:21:28.008586+00:00","updated_at":"2026-07-17T01:21:28.008586+00:00"}