{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:25CUZAWOU3HCE3Y5KHHKALQUUH","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":"68b5e87e0d41407b6512b1138570418123ddec3193f8ced0a8b4a74dc819958f","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-05T06:30:11Z","title_canon_sha256":"1d7bb99a57a6d1467626cac44ce2c0d95c27167b2e6e1c871c6c93cbcae7c1b1"},"schema_version":"1.0","source":{"id":"2506.04668","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.04668","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"arxiv_version","alias_value":"2506.04668v3","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.04668","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"pith_short_12","alias_value":"25CUZAWOU3HC","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"pith_short_16","alias_value":"25CUZAWOU3HCE3Y5","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"pith_short_8","alias_value":"25CUZAWO","created_at":"2026-07-05T11:18:23Z"}],"graph_snapshots":[{"event_id":"sha256:589662bc133428c6b76fb529aea2eca3e481e5bbfc993d8bb7f3a01d1ea96bdf","target":"graph","created_at":"2026-07-05T11:18:23Z","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/2506.04668/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The main goal of representation learning is to acquire meaningful representations from real-world sensory inputs without supervision. Representation learning explains some aspects of human development. Various neural network (NN) models have been proposed that acquire empirically good representations. However, the formulation of a good representation has not been established. We recently proposed a method for categorizing changes between a pair of sensory inputs. A unique feature of this approach is that transformations between two sensory inputs are learned to satisfy algebraic structural con","authors_text":"Kayato Nishitsunoi, Takayuki Komatsu, Yasuo Kuniyoshi, Yoshiyuki Ohmura","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-05T06:30:11Z","title":"Feature-Based Lie Group Transformer for Real-World Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.04668","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":"sha256:7af551ec327413795bfbfe902f4af11551d35152ee43f91e491c215e0d0d22e7","target":"record","created_at":"2026-07-05T11:18:23Z","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":"68b5e87e0d41407b6512b1138570418123ddec3193f8ced0a8b4a74dc819958f","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-05T06:30:11Z","title_canon_sha256":"1d7bb99a57a6d1467626cac44ce2c0d95c27167b2e6e1c871c6c93cbcae7c1b1"},"schema_version":"1.0","source":{"id":"2506.04668","kind":"arxiv","version":3}},"canonical_sha256":"d7454c82cea6ce226f1d51cea02e14a1f17258359dbb8de1602c5dcaeda6b22b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d7454c82cea6ce226f1d51cea02e14a1f17258359dbb8de1602c5dcaeda6b22b","first_computed_at":"2026-07-05T11:18:23.102240Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:18:23.102240Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Hs9Cj07gPAYkbQk5TGe8OygAO9jF5hsyMOGnZuSpiiCVXnbmAhBnBtVuPzSmrxQ9eCUXokdr8Mg3qbVFzo3cDg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:18:23.102743Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.04668","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7af551ec327413795bfbfe902f4af11551d35152ee43f91e491c215e0d0d22e7","sha256:589662bc133428c6b76fb529aea2eca3e481e5bbfc993d8bb7f3a01d1ea96bdf"],"state_sha256":"1c3dac62b0b4e949e0740bdfe56b3e6d17b4c8a9d1a4d87ddf80fc19b7629347"}