{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:YJMEEQI7V6QVPQQIRMQSGAS3QE","short_pith_number":"pith:YJMEEQI7","canonical_record":{"source":{"id":"2305.15270","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-24T15:56:26Z","cross_cats_sorted":[],"title_canon_sha256":"4094e5caa7e6350b07960605fc8ede0b3505028b5e3d0c8873862aee4dfad9e6","abstract_canon_sha256":"efce00e89581190cbb7900b68a6d46f3f03d010fd446691c40392c72611ab6e6"},"schema_version":"1.0"},"canonical_sha256":"c25842411fafa157c2088b2123025b8129b6a0f34cb5723eb91dd732adb8a622","source":{"kind":"arxiv","id":"2305.15270","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.15270","created_at":"2026-07-05T07:13:22Z"},{"alias_kind":"arxiv_version","alias_value":"2305.15270v3","created_at":"2026-07-05T07:13:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.15270","created_at":"2026-07-05T07:13:22Z"},{"alias_kind":"pith_short_12","alias_value":"YJMEEQI7V6QV","created_at":"2026-07-05T07:13:22Z"},{"alias_kind":"pith_short_16","alias_value":"YJMEEQI7V6QVPQQI","created_at":"2026-07-05T07:13:22Z"},{"alias_kind":"pith_short_8","alias_value":"YJMEEQI7","created_at":"2026-07-05T07:13:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:YJMEEQI7V6QVPQQIRMQSGAS3QE","target":"record","payload":{"canonical_record":{"source":{"id":"2305.15270","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-24T15:56:26Z","cross_cats_sorted":[],"title_canon_sha256":"4094e5caa7e6350b07960605fc8ede0b3505028b5e3d0c8873862aee4dfad9e6","abstract_canon_sha256":"efce00e89581190cbb7900b68a6d46f3f03d010fd446691c40392c72611ab6e6"},"schema_version":"1.0"},"canonical_sha256":"c25842411fafa157c2088b2123025b8129b6a0f34cb5723eb91dd732adb8a622","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:13:22.988344Z","signature_b64":"XrtlF1OiETk290jYduSRk9LK5S7A7tgnOMZPN2/dllbvxkifU6+6SCEil0KAl2jZ1L/P2Ega/2p1/TlD/BjtCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c25842411fafa157c2088b2123025b8129b6a0f34cb5723eb91dd732adb8a622","last_reissued_at":"2026-07-05T07:13:22.987909Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:13:22.987909Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.15270","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:13:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KrMJJhyWQNB0DMYBtKPpN9S2ZUgSLdNizwRlPil0Caha7weV/RSrzlMNBc0oYjcGdGfqooQTxKuYoZcPYH7iDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T16:51:11.598083Z"},"content_sha256":"f71ea0cadaaf10ab722f06d58ca1fdf78960abc47e8ec770c52865ee898599a5","schema_version":"1.0","event_id":"sha256:f71ea0cadaaf10ab722f06d58ca1fdf78960abc47e8ec770c52865ee898599a5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:YJMEEQI7V6QVPQQIRMQSGAS3QE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Reversible Graph Neural Network-based Reaction Distribution Learning for Multiple Appropriate Facial Reactions Generation","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hao Tang, Hatice Gunes, Lu Liu, Micol Spitale, Siyang Song, Tong Xu","submitted_at":"2023-05-24T15:56:26Z","abstract_excerpt":"Generating facial reactions in a human-human dyadic interaction is complex and highly dependent on the context since more than one facial reactions can be appropriate for the speaker's behaviour. This has challenged existing machine learning (ML) methods, whose training strategies enforce models to reproduce a specific (not multiple) facial reaction from each input speaker behaviour. This paper proposes the first multiple appropriate facial reaction generation framework that re-formulates the one-to-many mapping facial reaction generation problem as a one-to-one mapping problem. This means tha"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.15270","kind":"arxiv","version":3},"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/2305.15270/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":"2026-07-05T07:13:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aXmrzZxoPa+N2Tyki9kDiBGe6HQ6ZZB+bYQXwoxTIzR7SqQQJbWCEssbeFaVDdBN6y4TMDkRHnLnYLkPDVAtBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T16:51:11.598726Z"},"content_sha256":"8a5b6836267907ecca3ec601274b0b46fe2f5553fdbfd3fd4cd68c57bd3d18c4","schema_version":"1.0","event_id":"sha256:8a5b6836267907ecca3ec601274b0b46fe2f5553fdbfd3fd4cd68c57bd3d18c4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YJMEEQI7V6QVPQQIRMQSGAS3QE/bundle.json","state_url":"https://pith.science/pith/YJMEEQI7V6QVPQQIRMQSGAS3QE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YJMEEQI7V6QVPQQIRMQSGAS3QE/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":"2026-08-11T16:51:11Z","links":{"resolver":"https://pith.science/pith/YJMEEQI7V6QVPQQIRMQSGAS3QE","bundle":"https://pith.science/pith/YJMEEQI7V6QVPQQIRMQSGAS3QE/bundle.json","state":"https://pith.science/pith/YJMEEQI7V6QVPQQIRMQSGAS3QE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YJMEEQI7V6QVPQQIRMQSGAS3QE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:YJMEEQI7V6QVPQQIRMQSGAS3QE","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":"efce00e89581190cbb7900b68a6d46f3f03d010fd446691c40392c72611ab6e6","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-24T15:56:26Z","title_canon_sha256":"4094e5caa7e6350b07960605fc8ede0b3505028b5e3d0c8873862aee4dfad9e6"},"schema_version":"1.0","source":{"id":"2305.15270","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.15270","created_at":"2026-07-05T07:13:22Z"},{"alias_kind":"arxiv_version","alias_value":"2305.15270v3","created_at":"2026-07-05T07:13:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.15270","created_at":"2026-07-05T07:13:22Z"},{"alias_kind":"pith_short_12","alias_value":"YJMEEQI7V6QV","created_at":"2026-07-05T07:13:22Z"},{"alias_kind":"pith_short_16","alias_value":"YJMEEQI7V6QVPQQI","created_at":"2026-07-05T07:13:22Z"},{"alias_kind":"pith_short_8","alias_value":"YJMEEQI7","created_at":"2026-07-05T07:13:22Z"}],"graph_snapshots":[{"event_id":"sha256:8a5b6836267907ecca3ec601274b0b46fe2f5553fdbfd3fd4cd68c57bd3d18c4","target":"graph","created_at":"2026-07-05T07:13:22Z","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/2305.15270/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generating facial reactions in a human-human dyadic interaction is complex and highly dependent on the context since more than one facial reactions can be appropriate for the speaker's behaviour. This has challenged existing machine learning (ML) methods, whose training strategies enforce models to reproduce a specific (not multiple) facial reaction from each input speaker behaviour. This paper proposes the first multiple appropriate facial reaction generation framework that re-formulates the one-to-many mapping facial reaction generation problem as a one-to-one mapping problem. This means tha","authors_text":"Hao Tang, Hatice Gunes, Lu Liu, Micol Spitale, Siyang Song, Tong Xu","cross_cats":[],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-24T15:56:26Z","title":"Reversible Graph Neural Network-based Reaction Distribution Learning for Multiple Appropriate Facial Reactions Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.15270","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:f71ea0cadaaf10ab722f06d58ca1fdf78960abc47e8ec770c52865ee898599a5","target":"record","created_at":"2026-07-05T07:13:22Z","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":"efce00e89581190cbb7900b68a6d46f3f03d010fd446691c40392c72611ab6e6","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-24T15:56:26Z","title_canon_sha256":"4094e5caa7e6350b07960605fc8ede0b3505028b5e3d0c8873862aee4dfad9e6"},"schema_version":"1.0","source":{"id":"2305.15270","kind":"arxiv","version":3}},"canonical_sha256":"c25842411fafa157c2088b2123025b8129b6a0f34cb5723eb91dd732adb8a622","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c25842411fafa157c2088b2123025b8129b6a0f34cb5723eb91dd732adb8a622","first_computed_at":"2026-07-05T07:13:22.987909Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:13:22.987909Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XrtlF1OiETk290jYduSRk9LK5S7A7tgnOMZPN2/dllbvxkifU6+6SCEil0KAl2jZ1L/P2Ega/2p1/TlD/BjtCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:13:22.988344Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.15270","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f71ea0cadaaf10ab722f06d58ca1fdf78960abc47e8ec770c52865ee898599a5","sha256:8a5b6836267907ecca3ec601274b0b46fe2f5553fdbfd3fd4cd68c57bd3d18c4"],"state_sha256":"6be21b8a406f8e033dbae24cdc3f49bc0ebbe4296b210a5c91a24b4db070d738"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rcQa8jo9fKWhu7LYRARaQUVyjBcgkeZx9/SpZptZkyziEaDGaOWwSvt+C6miOnmABeqAcfFpIoF29YyQjqjJBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T16:51:11.605596Z","bundle_sha256":"d51d27b4e52d25f0463423a218386248b343bfa8f376203a8ba4fa4acf31f26e"}}