{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:BDTPKHEWJI2YWHW7HFIQIAQFHY","short_pith_number":"pith:BDTPKHEW","canonical_record":{"source":{"id":"2412.08468","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-12-11T15:33:35Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"7eda8c46747bc6a8001cbb4ae4bedce6eb813fd219f63cb2a56f6a2aaa53f307","abstract_canon_sha256":"1d6335e734c4fa6cbdfbafb155abde85d87872ab32ea3d90941715691c8d83c2"},"schema_version":"1.0"},"canonical_sha256":"08e6f51c964a358b1edf39510402053e03a420c478c4947bef5910a257a4d891","source":{"kind":"arxiv","id":"2412.08468","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.08468","created_at":"2026-07-05T11:17:38Z"},{"alias_kind":"arxiv_version","alias_value":"2412.08468v3","created_at":"2026-07-05T11:17:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.08468","created_at":"2026-07-05T11:17:38Z"},{"alias_kind":"pith_short_12","alias_value":"BDTPKHEWJI2Y","created_at":"2026-07-05T11:17:38Z"},{"alias_kind":"pith_short_16","alias_value":"BDTPKHEWJI2YWHW7","created_at":"2026-07-05T11:17:38Z"},{"alias_kind":"pith_short_8","alias_value":"BDTPKHEW","created_at":"2026-07-05T11:17:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:BDTPKHEWJI2YWHW7HFIQIAQFHY","target":"record","payload":{"canonical_record":{"source":{"id":"2412.08468","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-12-11T15:33:35Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"7eda8c46747bc6a8001cbb4ae4bedce6eb813fd219f63cb2a56f6a2aaa53f307","abstract_canon_sha256":"1d6335e734c4fa6cbdfbafb155abde85d87872ab32ea3d90941715691c8d83c2"},"schema_version":"1.0"},"canonical_sha256":"08e6f51c964a358b1edf39510402053e03a420c478c4947bef5910a257a4d891","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:17:38.916306Z","signature_b64":"6tSvNEp5uKFQP2M9BEEzgNH3EuJH3OnP+Z9f4/tSShcYNacbdZ7cSU+40CuCJxGirrpsuhGucubO4ahsukMvDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"08e6f51c964a358b1edf39510402053e03a420c478c4947bef5910a257a4d891","last_reissued_at":"2026-07-05T11:17:38.915539Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:17:38.915539Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.08468","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:17:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VI2XrFNczxEPCD2iqN480nCuYIhHnu6TAM/IQF61Mk1v4hErZDtu7u2Rp57ERYACQF72kLAjtV/HoqwPM99XAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T08:10:18.181764Z"},"content_sha256":"6ceaae2a6bc5f0f416ac1c183dce2038247728f4f8aa2f09e7c1846ffcd40578","schema_version":"1.0","event_id":"sha256:6ceaae2a6bc5f0f416ac1c183dce2038247728f4f8aa2f09e7c1846ffcd40578"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:BDTPKHEWJI2YWHW7HFIQIAQFHY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-GraspLLM: A Multimodal LLM for Multi-Hand Semantic Guided Grasp Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Chenyu Meng, Haoqiang Fan, Haosheng Li, Hongan Wang, Ping Tan, Tiancai Wang, Weipeng Deng, Weixin Mao, Xiaoming Deng, Yoshie Osamu","submitted_at":"2024-12-11T15:33:35Z","abstract_excerpt":"Multi-hand semantic grasp generation aims to generate feasible and semantically appropriate grasp poses for different robotic hands based on natural language instructions. Although the task is highly valuable, due to the lack of multihand grasp datasets with fine-grained contact description between robotic hands and objects, it is still a long-standing difficult task. In this paper, we present Multi-GraspSet, the first large-scale multi-hand grasp dataset with automatically contact annotations. Based on Multi-GraspSet, we propose Multi-GraspLLM, a unified language-guided grasp generation frame"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.08468","kind":"arxiv","version":3},"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/2412.08468/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:17:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"19KkaGxB2gARh9plwdo9Ocyr89L8C8g5fg4dzPWljHtGiHI6egEW8BZU6MbPyt2T3J3m83DLg7N/fqoIHXUdAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T08:10:18.182330Z"},"content_sha256":"e2044c3f3b30f8e6b2ab963e2c57a4a6a7bd3b8284219322bec0f3117b3cb53c","schema_version":"1.0","event_id":"sha256:e2044c3f3b30f8e6b2ab963e2c57a4a6a7bd3b8284219322bec0f3117b3cb53c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BDTPKHEWJI2YWHW7HFIQIAQFHY/bundle.json","state_url":"https://pith.science/pith/BDTPKHEWJI2YWHW7HFIQIAQFHY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BDTPKHEWJI2YWHW7HFIQIAQFHY/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-06T08:10:18Z","links":{"resolver":"https://pith.science/pith/BDTPKHEWJI2YWHW7HFIQIAQFHY","bundle":"https://pith.science/pith/BDTPKHEWJI2YWHW7HFIQIAQFHY/bundle.json","state":"https://pith.science/pith/BDTPKHEWJI2YWHW7HFIQIAQFHY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BDTPKHEWJI2YWHW7HFIQIAQFHY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:BDTPKHEWJI2YWHW7HFIQIAQFHY","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":"1d6335e734c4fa6cbdfbafb155abde85d87872ab32ea3d90941715691c8d83c2","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-12-11T15:33:35Z","title_canon_sha256":"7eda8c46747bc6a8001cbb4ae4bedce6eb813fd219f63cb2a56f6a2aaa53f307"},"schema_version":"1.0","source":{"id":"2412.08468","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.08468","created_at":"2026-07-05T11:17:38Z"},{"alias_kind":"arxiv_version","alias_value":"2412.08468v3","created_at":"2026-07-05T11:17:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.08468","created_at":"2026-07-05T11:17:38Z"},{"alias_kind":"pith_short_12","alias_value":"BDTPKHEWJI2Y","created_at":"2026-07-05T11:17:38Z"},{"alias_kind":"pith_short_16","alias_value":"BDTPKHEWJI2YWHW7","created_at":"2026-07-05T11:17:38Z"},{"alias_kind":"pith_short_8","alias_value":"BDTPKHEW","created_at":"2026-07-05T11:17:38Z"}],"graph_snapshots":[{"event_id":"sha256:e2044c3f3b30f8e6b2ab963e2c57a4a6a7bd3b8284219322bec0f3117b3cb53c","target":"graph","created_at":"2026-07-05T11:17:38Z","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/2412.08468/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-hand semantic grasp generation aims to generate feasible and semantically appropriate grasp poses for different robotic hands based on natural language instructions. Although the task is highly valuable, due to the lack of multihand grasp datasets with fine-grained contact description between robotic hands and objects, it is still a long-standing difficult task. In this paper, we present Multi-GraspSet, the first large-scale multi-hand grasp dataset with automatically contact annotations. Based on Multi-GraspSet, we propose Multi-GraspLLM, a unified language-guided grasp generation frame","authors_text":"Chenyu Meng, Haoqiang Fan, Haosheng Li, Hongan Wang, Ping Tan, Tiancai Wang, Weipeng Deng, Weixin Mao, Xiaoming Deng, Yoshie Osamu","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-12-11T15:33:35Z","title":"Multi-GraspLLM: A Multimodal LLM for Multi-Hand Semantic Guided Grasp Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.08468","kind":"arxiv","version":3},"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":"sha256:6ceaae2a6bc5f0f416ac1c183dce2038247728f4f8aa2f09e7c1846ffcd40578","target":"record","created_at":"2026-07-05T11:17:38Z","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":"1d6335e734c4fa6cbdfbafb155abde85d87872ab32ea3d90941715691c8d83c2","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-12-11T15:33:35Z","title_canon_sha256":"7eda8c46747bc6a8001cbb4ae4bedce6eb813fd219f63cb2a56f6a2aaa53f307"},"schema_version":"1.0","source":{"id":"2412.08468","kind":"arxiv","version":3}},"canonical_sha256":"08e6f51c964a358b1edf39510402053e03a420c478c4947bef5910a257a4d891","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"08e6f51c964a358b1edf39510402053e03a420c478c4947bef5910a257a4d891","first_computed_at":"2026-07-05T11:17:38.915539Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:17:38.915539Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6tSvNEp5uKFQP2M9BEEzgNH3EuJH3OnP+Z9f4/tSShcYNacbdZ7cSU+40CuCJxGirrpsuhGucubO4ahsukMvDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:17:38.916306Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.08468","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6ceaae2a6bc5f0f416ac1c183dce2038247728f4f8aa2f09e7c1846ffcd40578","sha256:e2044c3f3b30f8e6b2ab963e2c57a4a6a7bd3b8284219322bec0f3117b3cb53c"],"state_sha256":"7a5c71580d6c395a8e28c84762770b6eb41a2dd6cbb5d8ef723e61d6f3e56203"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VunF1zG4eKUfu8jTV+CxPkg/H8Jwp00OjzMpuvxWK4ID7WTsJEymfwD9LJA6k8ajnYwrUB1jB0OvgA3L41QNCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T08:10:18.187453Z","bundle_sha256":"62045241a77f6f96fa5bb50c1f7aa8006c95924e782e981b79b737f94ed6441b"}}