{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:B2IGCX6UYH3SZXPDEZSLJQQ5QT","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":"08ff24a0dcb5e70fb8c847f56fd7d21178696ee8b267d6215b781d50fb3288cf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T09:27:16Z","title_canon_sha256":"c44c90a0a1467d108b6e13774f505d489fe6150038cc8cf0b17b70ecf6c048b8"},"schema_version":"1.0","source":{"id":"2505.20941","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.20941","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"arxiv_version","alias_value":"2505.20941v1","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.20941","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"pith_short_12","alias_value":"B2IGCX6UYH3S","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"pith_short_16","alias_value":"B2IGCX6UYH3SZXPD","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"pith_short_8","alias_value":"B2IGCX6U","created_at":"2026-07-05T11:10:21Z"}],"graph_snapshots":[{"event_id":"sha256:95fac6d39b9a9165aaff22683452ed483e8959328890d4470798e75aa83f7fba","target":"graph","created_at":"2026-07-05T11:10:21Z","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/2505.20941/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Applying pre-trained models to assist point cloud understanding has recently become a mainstream paradigm in 3D perception. However, existing application strategies are straightforward, utilizing only the final output of the pre-trained model for various task heads. It neglects the rich complementary information in the intermediate layer, thereby failing to fully unlock the potential of pre-trained models. To overcome this limitation, we propose an orthogonal solution: Point Mamba Adapter (PMA), which constructs an ordered feature sequence from all layers of the pre-trained model and leverages","authors_text":"Bin Chen, Hang Guo, Jinpeng Wang, Ke Chen, Shu-Tao Xia, Tao Dai, Xue Yuerong, Yanzi Wang, Yaohua Zha, Zhihao Ouyang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T09:27:16Z","title":"PMA: Towards Parameter-Efficient Point Cloud Understanding via Point Mamba Adapter"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.20941","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:ab76158d700d743452d0ef4c2a19dd2af5352760394e6dc35dc41d7073c4d748","target":"record","created_at":"2026-07-05T11:10:21Z","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":"08ff24a0dcb5e70fb8c847f56fd7d21178696ee8b267d6215b781d50fb3288cf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T09:27:16Z","title_canon_sha256":"c44c90a0a1467d108b6e13774f505d489fe6150038cc8cf0b17b70ecf6c048b8"},"schema_version":"1.0","source":{"id":"2505.20941","kind":"arxiv","version":1}},"canonical_sha256":"0e90615fd4c1f72cdde32664b4c21d84f511315767233d4bff9993d0fb089ead","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0e90615fd4c1f72cdde32664b4c21d84f511315767233d4bff9993d0fb089ead","first_computed_at":"2026-07-05T11:10:21.357407Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:10:21.357407Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Jg4vIowP62QtgpzK40XkcGn8HLj34izRNp2vgtxKMlof47xLAEmIiX0J1ddSIzwPTnH5tE/XSqs32iRcYh8oCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:10:21.357964Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.20941","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ab76158d700d743452d0ef4c2a19dd2af5352760394e6dc35dc41d7073c4d748","sha256:95fac6d39b9a9165aaff22683452ed483e8959328890d4470798e75aa83f7fba"],"state_sha256":"045eb736ff08fac44b89bed33b3923429203ec0b0666de77e934e9832554ff1c"}