{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:AQJE3BX3JTPFVIPSLGT235RAON","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":"e479ec63666b6b81a98f7e7d9a10336883ce95c543d3afa1e5c11cce86198305","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-09-19T07:52:02Z","title_canon_sha256":"562fca09d4ebd1f5f89e0e8d7315f14ccae4883b4673f29a7c08aa0ef864fc27"},"schema_version":"1.0","source":{"id":"2209.08812","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.08812","created_at":"2026-07-05T10:04:09Z"},{"alias_kind":"arxiv_version","alias_value":"2209.08812v5","created_at":"2026-07-05T10:04:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.08812","created_at":"2026-07-05T10:04:09Z"},{"alias_kind":"pith_short_12","alias_value":"AQJE3BX3JTPF","created_at":"2026-07-05T10:04:09Z"},{"alias_kind":"pith_short_16","alias_value":"AQJE3BX3JTPFVIPS","created_at":"2026-07-05T10:04:09Z"},{"alias_kind":"pith_short_8","alias_value":"AQJE3BX3","created_at":"2026-07-05T10:04:09Z"}],"graph_snapshots":[{"event_id":"sha256:fd2c397b1e6b6a1cd840c8003805eb592f38b03fd5406c0f0cf579d303a4d423","target":"graph","created_at":"2026-07-05T10:04:09Z","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/2209.08812/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Quickly and reliably finding accurate inverse kinematics (IK) solutions remains a challenging problem for many robot manipulators. Existing numerical solvers are broadly applicable but typically only produce a single solution and rely on local search techniques to minimize nonconvex objective functions. More recent learning-based approaches that approximate the entire feasible set of solutions have shown promise as a means to generate multiple fast and accurate IK results in parallel. However, existing learning-based techniques have a significant drawback: each robot of interest requires a spe","authors_text":"Filip Mari\\'c, Ivan Petrovi\\'c, Jonathan Kelly, Matthew Giamou, Oliver Limoyo, Petra Alexson","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-09-19T07:52:02Z","title":"Generative Graphical Inverse Kinematics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.08812","kind":"arxiv","version":5},"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":"sha256:45b594c2917c1cc8a08e87bf5c15ed1d26dfc97eccb88ed2042bbb8081a82308","target":"record","created_at":"2026-07-05T10:04:09Z","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":"e479ec63666b6b81a98f7e7d9a10336883ce95c543d3afa1e5c11cce86198305","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-09-19T07:52:02Z","title_canon_sha256":"562fca09d4ebd1f5f89e0e8d7315f14ccae4883b4673f29a7c08aa0ef864fc27"},"schema_version":"1.0","source":{"id":"2209.08812","kind":"arxiv","version":5}},"canonical_sha256":"04124d86fb4cde5aa1f259a7adf620737ca8be1cde2cc5200f4604b5683c510a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"04124d86fb4cde5aa1f259a7adf620737ca8be1cde2cc5200f4604b5683c510a","first_computed_at":"2026-07-05T10:04:09.224212Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:04:09.224212Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e4jyForilAYWukEx0QjUksuXYgy83pku1aX6ZRnb8qVoWES9g3AHm8UX9/YJWSErHW1443idgvlAAu0c8YPTBg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:04:09.224701Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.08812","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:45b594c2917c1cc8a08e87bf5c15ed1d26dfc97eccb88ed2042bbb8081a82308","sha256:fd2c397b1e6b6a1cd840c8003805eb592f38b03fd5406c0f0cf579d303a4d423"],"state_sha256":"7903cb55878c23411be873117ec9f7032ec2ab0e24cfc508ad3b0c3b5d387a0e"}