{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:3R5VEF4A3D3UETGOFU47DQBPLF","short_pith_number":"pith:3R5VEF4A","canonical_record":{"source":{"id":"2607.29180","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-31T09:01:25Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"fe415aa87510ac256fe133b652c1265602e8d5c6205920b1a478c5dca0d657dc","abstract_canon_sha256":"f2377dd072a70dc744bfcb8c4a4f0f430e2da19b6e313164a96ffbd64adec6cf"},"schema_version":"1.0"},"canonical_sha256":"dc7b521780d8f7424cce2d39f1c02f59754b689df673049100c7d82e8792ad2d","source":{"kind":"arxiv","id":"2607.29180","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.29180","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"arxiv_version","alias_value":"2607.29180v1","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.29180","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"pith_short_12","alias_value":"3R5VEF4A3D3U","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"pith_short_16","alias_value":"3R5VEF4A3D3UETGO","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"pith_short_8","alias_value":"3R5VEF4A","created_at":"2026-08-03T01:20:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:3R5VEF4A3D3UETGOFU47DQBPLF","target":"record","payload":{"canonical_record":{"source":{"id":"2607.29180","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-31T09:01:25Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"fe415aa87510ac256fe133b652c1265602e8d5c6205920b1a478c5dca0d657dc","abstract_canon_sha256":"f2377dd072a70dc744bfcb8c4a4f0f430e2da19b6e313164a96ffbd64adec6cf"},"schema_version":"1.0"},"canonical_sha256":"dc7b521780d8f7424cce2d39f1c02f59754b689df673049100c7d82e8792ad2d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-03T01:20:29.760260Z","signature_b64":"x5Ul7eyfT4uRr2RjcMVmXtoWRcSWtOyI8/zrmmnMkMu/J9/ijmxrPbb8lz9O9M4EgJ/4/NNuIGrZt7JX7dmDDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dc7b521780d8f7424cce2d39f1c02f59754b689df673049100c7d82e8792ad2d","last_reissued_at":"2026-08-03T01:20:29.758653Z","signature_status":"signed_v1","first_computed_at":"2026-08-03T01:20:29.758653Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.29180","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-03T01:20:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bGYIonD+pXtRJCqr4xO2GUk3aoUHu97ZdojRoEsnhpU+H1FGPvkrcyNJ4nuTmS4QYcNdbfq5Nn/T4nPKX2nvBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T04:15:56.814554Z"},"content_sha256":"b338125bb29765cc26c97094ba1f22438ec4c24ee8c8adf2572694e9fcd565ac","schema_version":"1.0","event_id":"sha256:b338125bb29765cc26c97094ba1f22438ec4c24ee8c8adf2572694e9fcd565ac"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:3R5VEF4A3D3UETGOFU47DQBPLF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MoRAE: Flow-Friendly Self-Supervised Latents for Text-to-Motion Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Miao Cheng, Mingyi Shi, Taku Komura, Yangyang Cai, Yifei Zhu, Yoshifumi Kitamura","submitted_at":"2026-07-31T09:01:25Z","abstract_excerpt":"Text-to-motion generation must produce motions that are semantically correct, temporally coherent, and physically plausible. A natural approach is to first project motion data into a structured semantic space and then train a generative model within that space. Such a paradigm has been highly successful in image generation through Representation Autoencoders (RAEs), where a frozen self-supervised encoder provides semantic features for diffusion or flow models to learn from. However, direct transfer of such a paradigm to motion space using Motion-JEPA as the frozen encoder fails dramatically. W"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.29180","kind":"arxiv","version":1},"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/2607.29180/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":"2026-08-03T01:20:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fCoOmysXgaugE5gCWyb9sxgFCAou+ledqDIX+I3Fn7ThCb8OcNIVE7SMMdVvdkxF0kOARK0flsA1pWYD8xhyDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T04:15:56.815475Z"},"content_sha256":"fa4f8688b5906d63ca143975812663b59dff45d0eea437edcd55f7522916a183","schema_version":"1.0","event_id":"sha256:fa4f8688b5906d63ca143975812663b59dff45d0eea437edcd55f7522916a183"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3R5VEF4A3D3UETGOFU47DQBPLF/bundle.json","state_url":"https://pith.science/pith/3R5VEF4A3D3UETGOFU47DQBPLF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3R5VEF4A3D3UETGOFU47DQBPLF/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":"2026-08-04T04:15:56Z","links":{"resolver":"https://pith.science/pith/3R5VEF4A3D3UETGOFU47DQBPLF","bundle":"https://pith.science/pith/3R5VEF4A3D3UETGOFU47DQBPLF/bundle.json","state":"https://pith.science/pith/3R5VEF4A3D3UETGOFU47DQBPLF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3R5VEF4A3D3UETGOFU47DQBPLF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:3R5VEF4A3D3UETGOFU47DQBPLF","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":"f2377dd072a70dc744bfcb8c4a4f0f430e2da19b6e313164a96ffbd64adec6cf","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-31T09:01:25Z","title_canon_sha256":"fe415aa87510ac256fe133b652c1265602e8d5c6205920b1a478c5dca0d657dc"},"schema_version":"1.0","source":{"id":"2607.29180","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.29180","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"arxiv_version","alias_value":"2607.29180v1","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.29180","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"pith_short_12","alias_value":"3R5VEF4A3D3U","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"pith_short_16","alias_value":"3R5VEF4A3D3UETGO","created_at":"2026-08-03T01:20:29Z"},{"alias_kind":"pith_short_8","alias_value":"3R5VEF4A","created_at":"2026-08-03T01:20:29Z"}],"graph_snapshots":[{"event_id":"sha256:fa4f8688b5906d63ca143975812663b59dff45d0eea437edcd55f7522916a183","target":"graph","created_at":"2026-08-03T01:20:29Z","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/2607.29180/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Text-to-motion generation must produce motions that are semantically correct, temporally coherent, and physically plausible. A natural approach is to first project motion data into a structured semantic space and then train a generative model within that space. Such a paradigm has been highly successful in image generation through Representation Autoencoders (RAEs), where a frozen self-supervised encoder provides semantic features for diffusion or flow models to learn from. However, direct transfer of such a paradigm to motion space using Motion-JEPA as the frozen encoder fails dramatically. W","authors_text":"Miao Cheng, Mingyi Shi, Taku Komura, Yangyang Cai, Yifei Zhu, Yoshifumi Kitamura","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-31T09:01:25Z","title":"MoRAE: Flow-Friendly Self-Supervised Latents for Text-to-Motion Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.29180","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:b338125bb29765cc26c97094ba1f22438ec4c24ee8c8adf2572694e9fcd565ac","target":"record","created_at":"2026-08-03T01:20:29Z","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":"f2377dd072a70dc744bfcb8c4a4f0f430e2da19b6e313164a96ffbd64adec6cf","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-31T09:01:25Z","title_canon_sha256":"fe415aa87510ac256fe133b652c1265602e8d5c6205920b1a478c5dca0d657dc"},"schema_version":"1.0","source":{"id":"2607.29180","kind":"arxiv","version":1}},"canonical_sha256":"dc7b521780d8f7424cce2d39f1c02f59754b689df673049100c7d82e8792ad2d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dc7b521780d8f7424cce2d39f1c02f59754b689df673049100c7d82e8792ad2d","first_computed_at":"2026-08-03T01:20:29.758653Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-03T01:20:29.758653Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"x5Ul7eyfT4uRr2RjcMVmXtoWRcSWtOyI8/zrmmnMkMu/J9/ijmxrPbb8lz9O9M4EgJ/4/NNuIGrZt7JX7dmDDg==","signature_status":"signed_v1","signed_at":"2026-08-03T01:20:29.760260Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.29180","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b338125bb29765cc26c97094ba1f22438ec4c24ee8c8adf2572694e9fcd565ac","sha256:fa4f8688b5906d63ca143975812663b59dff45d0eea437edcd55f7522916a183"],"state_sha256":"d664f3b31a4bf8bb9a5b0e4d919c2e0bf62376d0244b272839ef3802ed4d2a28"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X5NIjsQLRXgAqFNa+Haz9hw4AKgaaMeyL6uFd2su2eZdbe04iLUsnhQHhKqeQ/+X98p1v+BtTGfKiX1zztCjCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T04:15:56.820666Z","bundle_sha256":"97cc4a0bccfd8e51fc157799f2c4690e7c7e6a44310a2c4d9c1b9b7277746f85"}}