{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:4ECNRQETWFYTE4DA4CYBOEF6BZ","short_pith_number":"pith:4ECNRQET","canonical_record":{"source":{"id":"2511.10254","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-11-13T12:40:21Z","cross_cats_sorted":[],"title_canon_sha256":"5b0c297ed54ad1972f54f71e7c905e77aa7c5ebd6b491bdb3e5c22e191a41d3f","abstract_canon_sha256":"b59f2fd210a489e4c0cf6000abfb9ca056d6627f723aa7fc456b410337ac73c9"},"schema_version":"1.0"},"canonical_sha256":"e104d8c093b171327060e0b01710be0e53cd3054666cc92f5d652f4742f90fcf","source":{"kind":"arxiv","id":"2511.10254","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2511.10254","created_at":"2026-06-05T01:14:30Z"},{"alias_kind":"arxiv_version","alias_value":"2511.10254v2","created_at":"2026-06-05T01:14:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.10254","created_at":"2026-06-05T01:14:30Z"},{"alias_kind":"pith_short_12","alias_value":"4ECNRQETWFYT","created_at":"2026-06-05T01:14:30Z"},{"alias_kind":"pith_short_16","alias_value":"4ECNRQETWFYTE4DA","created_at":"2026-06-05T01:14:30Z"},{"alias_kind":"pith_short_8","alias_value":"4ECNRQET","created_at":"2026-06-05T01:14:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:4ECNRQETWFYTE4DA4CYBOEF6BZ","target":"record","payload":{"canonical_record":{"source":{"id":"2511.10254","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-11-13T12:40:21Z","cross_cats_sorted":[],"title_canon_sha256":"5b0c297ed54ad1972f54f71e7c905e77aa7c5ebd6b491bdb3e5c22e191a41d3f","abstract_canon_sha256":"b59f2fd210a489e4c0cf6000abfb9ca056d6627f723aa7fc456b410337ac73c9"},"schema_version":"1.0"},"canonical_sha256":"e104d8c093b171327060e0b01710be0e53cd3054666cc92f5d652f4742f90fcf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-05T01:14:30.837577Z","signature_b64":"sRM2j68ko1vZcSacSuC1CsdtzrMrFwxpdAG66VDbaFcaoFpw7jA/InsrgRzzYRZbg85K/Otw5i3lYjCT5YNBCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e104d8c093b171327060e0b01710be0e53cd3054666cc92f5d652f4742f90fcf","last_reissued_at":"2026-06-05T01:14:30.836883Z","signature_status":"signed_v1","first_computed_at":"2026-06-05T01:14:30.836883Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2511.10254","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":"2026-06-05T01:14:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l9HSlOF7DV6VskRBHIE59FVQWX8xEjKPYYWGvkFSwa1sgV1wobMX5y+YWBpBzCkK7A8K+tWhPXmQE+/XKPNKBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T16:30:38.298338Z"},"content_sha256":"1c7e75b935fc92f73b998ed57787bf4d425f78796e4d7107a85c315d5b84a81a","schema_version":"1.0","event_id":"sha256:1c7e75b935fc92f73b998ed57787bf4d425f78796e4d7107a85c315d5b84a81a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:4ECNRQETWFYTE4DA4CYBOEF6BZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Facial-R1: Aligning Reasoning and Recognition for Facial Emotion Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Deguo Xia, Haixin Sun, Jiulong Wu, Jizhou Huang, Lingyong Yan, Min Cao, Yucheng Shen","submitted_at":"2025-11-13T12:40:21Z","abstract_excerpt":"Facial Emotion Analysis (FEA) extends traditional facial emotion recognition by incorporating explainable, fine-grained reasoning. The task integrates three subtasks: emotion recognition, facial Action Unit (AU) recognition, and AU-based emotion reasoning to model affective states jointly. While recent approaches leverage Vision-Language Models (VLMs) and achieve promising results, they face two critical limitations: (1) hallucinated reasoning, where VLMs generate plausible but inaccurate explanations due to insufficient emotion-specific knowledge; and (2) misalignment between emotion reasonin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.10254","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/2511.10254/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":"2026-06-05T01:14:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KgAYY2/DMtl+qc7FT61Y8Z8esS7ON6tK4IDC0opnA77Awk4xZSiYsyfYax712yycM8fgMdC2zJvN5f3n9aolCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T16:30:38.299046Z"},"content_sha256":"f70b93e4f6342a9f76301eceae89321b2a2c96eae9df7de3d079739f22bfc7a2","schema_version":"1.0","event_id":"sha256:f70b93e4f6342a9f76301eceae89321b2a2c96eae9df7de3d079739f22bfc7a2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4ECNRQETWFYTE4DA4CYBOEF6BZ/bundle.json","state_url":"https://pith.science/pith/4ECNRQETWFYTE4DA4CYBOEF6BZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4ECNRQETWFYTE4DA4CYBOEF6BZ/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":"2026-06-06T16:30:38Z","links":{"resolver":"https://pith.science/pith/4ECNRQETWFYTE4DA4CYBOEF6BZ","bundle":"https://pith.science/pith/4ECNRQETWFYTE4DA4CYBOEF6BZ/bundle.json","state":"https://pith.science/pith/4ECNRQETWFYTE4DA4CYBOEF6BZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4ECNRQETWFYTE4DA4CYBOEF6BZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4ECNRQETWFYTE4DA4CYBOEF6BZ","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":"b59f2fd210a489e4c0cf6000abfb9ca056d6627f723aa7fc456b410337ac73c9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-11-13T12:40:21Z","title_canon_sha256":"5b0c297ed54ad1972f54f71e7c905e77aa7c5ebd6b491bdb3e5c22e191a41d3f"},"schema_version":"1.0","source":{"id":"2511.10254","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2511.10254","created_at":"2026-06-05T01:14:30Z"},{"alias_kind":"arxiv_version","alias_value":"2511.10254v2","created_at":"2026-06-05T01:14:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.10254","created_at":"2026-06-05T01:14:30Z"},{"alias_kind":"pith_short_12","alias_value":"4ECNRQETWFYT","created_at":"2026-06-05T01:14:30Z"},{"alias_kind":"pith_short_16","alias_value":"4ECNRQETWFYTE4DA","created_at":"2026-06-05T01:14:30Z"},{"alias_kind":"pith_short_8","alias_value":"4ECNRQET","created_at":"2026-06-05T01:14:30Z"}],"graph_snapshots":[{"event_id":"sha256:f70b93e4f6342a9f76301eceae89321b2a2c96eae9df7de3d079739f22bfc7a2","target":"graph","created_at":"2026-06-05T01:14:30Z","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/2511.10254/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Facial Emotion Analysis (FEA) extends traditional facial emotion recognition by incorporating explainable, fine-grained reasoning. The task integrates three subtasks: emotion recognition, facial Action Unit (AU) recognition, and AU-based emotion reasoning to model affective states jointly. While recent approaches leverage Vision-Language Models (VLMs) and achieve promising results, they face two critical limitations: (1) hallucinated reasoning, where VLMs generate plausible but inaccurate explanations due to insufficient emotion-specific knowledge; and (2) misalignment between emotion reasonin","authors_text":"Deguo Xia, Haixin Sun, Jiulong Wu, Jizhou Huang, Lingyong Yan, Min Cao, Yucheng Shen","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-11-13T12:40:21Z","title":"Facial-R1: Aligning Reasoning and Recognition for Facial Emotion Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.10254","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":"sha256:1c7e75b935fc92f73b998ed57787bf4d425f78796e4d7107a85c315d5b84a81a","target":"record","created_at":"2026-06-05T01:14:30Z","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":"b59f2fd210a489e4c0cf6000abfb9ca056d6627f723aa7fc456b410337ac73c9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-11-13T12:40:21Z","title_canon_sha256":"5b0c297ed54ad1972f54f71e7c905e77aa7c5ebd6b491bdb3e5c22e191a41d3f"},"schema_version":"1.0","source":{"id":"2511.10254","kind":"arxiv","version":2}},"canonical_sha256":"e104d8c093b171327060e0b01710be0e53cd3054666cc92f5d652f4742f90fcf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e104d8c093b171327060e0b01710be0e53cd3054666cc92f5d652f4742f90fcf","first_computed_at":"2026-06-05T01:14:30.836883Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-05T01:14:30.836883Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sRM2j68ko1vZcSacSuC1CsdtzrMrFwxpdAG66VDbaFcaoFpw7jA/InsrgRzzYRZbg85K/Otw5i3lYjCT5YNBCQ==","signature_status":"signed_v1","signed_at":"2026-06-05T01:14:30.837577Z","signed_message":"canonical_sha256_bytes"},"source_id":"2511.10254","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1c7e75b935fc92f73b998ed57787bf4d425f78796e4d7107a85c315d5b84a81a","sha256:f70b93e4f6342a9f76301eceae89321b2a2c96eae9df7de3d079739f22bfc7a2"],"state_sha256":"ec507b4955b9aef5e33a1c7a4d68ca8d152f9ee9203255ee31a68bfa308632a6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NSdv0zAMY+JC1JIv2OiJiqcIiGwiRQDx5iTt35eJqLAgM+c5bZrmUa8o77ii4Ep7h1ldaT236b+sYAKa+tDYDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T16:30:38.302284Z","bundle_sha256":"b2413f4d3c2e93df11382495171e104259d6a7cc274ad97a5ff913b649163331"}}