{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:VFT2EAGZDUV52WBGYOJZA2TLQP","short_pith_number":"pith:VFT2EAGZ","canonical_record":{"source":{"id":"2503.10096","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-13T06:43:21Z","cross_cats_sorted":[],"title_canon_sha256":"b630e812de92de019ae73cacdc9a7f28c08fef36182a61ea0229dd17194a6d24","abstract_canon_sha256":"af4bc63286d07839dd3afedebdf794a2ce19dcaa84309185df4eafb82bed8066"},"schema_version":"1.0"},"canonical_sha256":"a967a200d91d2bdd5826c393906a6b83c382fb35b04924a3e84f623297a5c75c","source":{"kind":"arxiv","id":"2503.10096","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.10096","created_at":"2026-07-05T11:20:51Z"},{"alias_kind":"arxiv_version","alias_value":"2503.10096v2","created_at":"2026-07-05T11:20:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.10096","created_at":"2026-07-05T11:20:51Z"},{"alias_kind":"pith_short_12","alias_value":"VFT2EAGZDUV5","created_at":"2026-07-05T11:20:51Z"},{"alias_kind":"pith_short_16","alias_value":"VFT2EAGZDUV52WBG","created_at":"2026-07-05T11:20:51Z"},{"alias_kind":"pith_short_8","alias_value":"VFT2EAGZ","created_at":"2026-07-05T11:20:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:VFT2EAGZDUV52WBGYOJZA2TLQP","target":"record","payload":{"canonical_record":{"source":{"id":"2503.10096","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-13T06:43:21Z","cross_cats_sorted":[],"title_canon_sha256":"b630e812de92de019ae73cacdc9a7f28c08fef36182a61ea0229dd17194a6d24","abstract_canon_sha256":"af4bc63286d07839dd3afedebdf794a2ce19dcaa84309185df4eafb82bed8066"},"schema_version":"1.0"},"canonical_sha256":"a967a200d91d2bdd5826c393906a6b83c382fb35b04924a3e84f623297a5c75c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:20:51.567181Z","signature_b64":"7BgY39Ikw8NHI+5sdk3rplf1vRClCZBuZ3HGQXEcaCU5jICbdMUi09zPzreMZxK2zwtO3WbNKFMwJHn+alMIAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a967a200d91d2bdd5826c393906a6b83c382fb35b04924a3e84f623297a5c75c","last_reissued_at":"2026-07-05T11:20:51.566676Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:20:51.566676Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.10096","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:20:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IA8HE2f1vyIqsu/LhfyOCVpfnmPrO9LsUswp7jXLZzTEhepkZ/vFtUjC1yXxjT3A+Fu3GjHC4xaLZBCEsjTfBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T08:27:37.529468Z"},"content_sha256":"7fdbce6cd1e6a0047cfc22a31bddeb5ff58b7c33435a46949fbc2560ed1bd212","schema_version":"1.0","event_id":"sha256:7fdbce6cd1e6a0047cfc22a31bddeb5ff58b7c33435a46949fbc2560ed1bd212"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:VFT2EAGZDUV52WBGYOJZA2TLQP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Self-supervised Motion Representation for Portrait Video Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Changqing Zou, Chenyu Wu, Donglin Di, Huaize Liu, Qiyuan Zhang, Wei Chen, Wenzhang Sun","submitted_at":"2025-03-13T06:43:21Z","abstract_excerpt":"Recent advancements in portrait video generation have been noteworthy. However, existing methods rely heavily on human priors and pre-trained generative models, Motion representations based on human priors may introduce unrealistic motion, while methods relying on pre-trained generative models often suffer from inefficient inference. To address these challenges, we propose Semantic Latent Motion (SeMo), a compact and expressive motion representation. Leveraging this representation, our approach achieve both high-quality visual results and efficient inference. SeMo follows an effective three-st"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.10096","kind":"arxiv","version":2},"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/2503.10096/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":"2026-07-05T11:20:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a1f2CmSok8Mv8CvF0H/Jr45npdo2tMLqQdVVARU8sXeVErecx+6/SSR5AnWPTItNDehI3EP+9pzJL9RtHVTOBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T08:27:37.529841Z"},"content_sha256":"175fe1718d07b0c8b4421e9877059c598cdccb486841655a96e05e3ac10ac44c","schema_version":"1.0","event_id":"sha256:175fe1718d07b0c8b4421e9877059c598cdccb486841655a96e05e3ac10ac44c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VFT2EAGZDUV52WBGYOJZA2TLQP/bundle.json","state_url":"https://pith.science/pith/VFT2EAGZDUV52WBGYOJZA2TLQP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VFT2EAGZDUV52WBGYOJZA2TLQP/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":"2026-07-07T08:27:37Z","links":{"resolver":"https://pith.science/pith/VFT2EAGZDUV52WBGYOJZA2TLQP","bundle":"https://pith.science/pith/VFT2EAGZDUV52WBGYOJZA2TLQP/bundle.json","state":"https://pith.science/pith/VFT2EAGZDUV52WBGYOJZA2TLQP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VFT2EAGZDUV52WBGYOJZA2TLQP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VFT2EAGZDUV52WBGYOJZA2TLQP","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":"af4bc63286d07839dd3afedebdf794a2ce19dcaa84309185df4eafb82bed8066","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-13T06:43:21Z","title_canon_sha256":"b630e812de92de019ae73cacdc9a7f28c08fef36182a61ea0229dd17194a6d24"},"schema_version":"1.0","source":{"id":"2503.10096","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.10096","created_at":"2026-07-05T11:20:51Z"},{"alias_kind":"arxiv_version","alias_value":"2503.10096v2","created_at":"2026-07-05T11:20:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.10096","created_at":"2026-07-05T11:20:51Z"},{"alias_kind":"pith_short_12","alias_value":"VFT2EAGZDUV5","created_at":"2026-07-05T11:20:51Z"},{"alias_kind":"pith_short_16","alias_value":"VFT2EAGZDUV52WBG","created_at":"2026-07-05T11:20:51Z"},{"alias_kind":"pith_short_8","alias_value":"VFT2EAGZ","created_at":"2026-07-05T11:20:51Z"}],"graph_snapshots":[{"event_id":"sha256:175fe1718d07b0c8b4421e9877059c598cdccb486841655a96e05e3ac10ac44c","target":"graph","created_at":"2026-07-05T11:20:51Z","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/2503.10096/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advancements in portrait video generation have been noteworthy. However, existing methods rely heavily on human priors and pre-trained generative models, Motion representations based on human priors may introduce unrealistic motion, while methods relying on pre-trained generative models often suffer from inefficient inference. To address these challenges, we propose Semantic Latent Motion (SeMo), a compact and expressive motion representation. Leveraging this representation, our approach achieve both high-quality visual results and efficient inference. SeMo follows an effective three-st","authors_text":"Changqing Zou, Chenyu Wu, Donglin Di, Huaize Liu, Qiyuan Zhang, Wei Chen, Wenzhang Sun","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-13T06:43:21Z","title":"A Self-supervised Motion Representation for Portrait Video Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.10096","kind":"arxiv","version":2},"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":"sha256:7fdbce6cd1e6a0047cfc22a31bddeb5ff58b7c33435a46949fbc2560ed1bd212","target":"record","created_at":"2026-07-05T11:20:51Z","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":"af4bc63286d07839dd3afedebdf794a2ce19dcaa84309185df4eafb82bed8066","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-13T06:43:21Z","title_canon_sha256":"b630e812de92de019ae73cacdc9a7f28c08fef36182a61ea0229dd17194a6d24"},"schema_version":"1.0","source":{"id":"2503.10096","kind":"arxiv","version":2}},"canonical_sha256":"a967a200d91d2bdd5826c393906a6b83c382fb35b04924a3e84f623297a5c75c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a967a200d91d2bdd5826c393906a6b83c382fb35b04924a3e84f623297a5c75c","first_computed_at":"2026-07-05T11:20:51.566676Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:20:51.566676Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7BgY39Ikw8NHI+5sdk3rplf1vRClCZBuZ3HGQXEcaCU5jICbdMUi09zPzreMZxK2zwtO3WbNKFMwJHn+alMIAw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:20:51.567181Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.10096","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7fdbce6cd1e6a0047cfc22a31bddeb5ff58b7c33435a46949fbc2560ed1bd212","sha256:175fe1718d07b0c8b4421e9877059c598cdccb486841655a96e05e3ac10ac44c"],"state_sha256":"e83606f9ea1e998905dbc36666e1e4f44d3e68a7476b0104d23b40277860eda9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Tp2V/E0couLtW95KHXI4VcEwZPOvTnwzMwlRfp3umQwJQiNr5MjXMcSF6pKLzYoXQs1g08usTwQdam2x0zWMBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T08:27:37.531796Z","bundle_sha256":"1b388215ebc459470fb1456914b69b37f0e00c7b316859c602718cbfd375ddc6"}}