{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:C46MMESRRDNREND74ERHCO2D7R","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":"48f300a608c236efdba6addcbaae377fcfaf270f14dcb54ce3adbc473dcd6e13","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-07-03T14:36:45Z","title_canon_sha256":"8014e88a36b158c00f89a0847424d8c1253dc77a69d4258594a148d1b861f075"},"schema_version":"1.0","source":{"id":"2507.02672","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.02672","created_at":"2026-07-05T11:31:32Z"},{"alias_kind":"arxiv_version","alias_value":"2507.02672v1","created_at":"2026-07-05T11:31:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.02672","created_at":"2026-07-05T11:31:32Z"},{"alias_kind":"pith_short_12","alias_value":"C46MMESRRDNR","created_at":"2026-07-05T11:31:32Z"},{"alias_kind":"pith_short_16","alias_value":"C46MMESRRDNREND7","created_at":"2026-07-05T11:31:32Z"},{"alias_kind":"pith_short_8","alias_value":"C46MMESR","created_at":"2026-07-05T11:31:32Z"}],"graph_snapshots":[{"event_id":"sha256:a3e4161698ca9f7b75900dc10096609b2c03ab9eb708189b6f81a26e3e55ec57","target":"graph","created_at":"2026-07-05T11:31:32Z","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":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2507.02672/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Robotic grasping faces challenges in adapting to objects with varying shapes and sizes. In this paper, we introduce MISCGrasp, a volumetric grasping method that integrates multi-scale feature extraction with contrastive feature enhancement for self-adaptive grasping. We propose a query-based interaction between high-level and low-level features through the Insight Transformer, while the Empower Transformer selectively attends to the highest-level features, which synergistically strikes a balance between focusing on fine geometric details and overall geometric structures. Furthermore, MISCGrasp","authors_text":"Bin Liang, Chao Li, Chunting Jiao, Qingyu Fan, Shuo Wang, Tao Lu, Xudong Zheng, Yinghao Cai","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-07-03T14:36:45Z","title":"MISCGrasp: Leveraging Multiple Integrated Scales and Contrastive Learning for Enhanced Volumetric Grasping"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.02672","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:c5b0ca89a7296e7b2213049c8794e07f2df77931c10b065dd0016bc69695b400","target":"record","created_at":"2026-07-05T11:31:32Z","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":"48f300a608c236efdba6addcbaae377fcfaf270f14dcb54ce3adbc473dcd6e13","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-07-03T14:36:45Z","title_canon_sha256":"8014e88a36b158c00f89a0847424d8c1253dc77a69d4258594a148d1b861f075"},"schema_version":"1.0","source":{"id":"2507.02672","kind":"arxiv","version":1}},"canonical_sha256":"173cc6125188db12347fe122713b43fc492b9ccf4134bc93193ea05e994182b8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"173cc6125188db12347fe122713b43fc492b9ccf4134bc93193ea05e994182b8","first_computed_at":"2026-07-05T11:31:32.822442Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:31:32.822442Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KSL6VZOqWEQAv6R3wgZlQfKpkm4Gm2LfQLFD66kf0ZxRRzeFfq/Go3bccB4IJ3CoXQYQc6AhyJy+kv/lDLvCAg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:31:32.822834Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.02672","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c5b0ca89a7296e7b2213049c8794e07f2df77931c10b065dd0016bc69695b400","sha256:a3e4161698ca9f7b75900dc10096609b2c03ab9eb708189b6f81a26e3e55ec57"],"state_sha256":"2aa3bb81cfda5be945446b1f425d9208a73a731c2bf02c081c90361c3538b331"}