{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:OQQ2Q7VFRFTW5R4U6COD6R4V4A","short_pith_number":"pith:OQQ2Q7VF","canonical_record":{"source":{"id":"2506.13971","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2025-06-01T01:09:08Z","cross_cats_sorted":["cs.CL","cs.HC","cs.LG","cs.MM"],"title_canon_sha256":"348cedcd12c772280c3075f73fa7a5aa205a45123ce52f1b26abfaf5ae550748","abstract_canon_sha256":"f03d7621c2a7f31c19ab906f1596d7ef884e4c57905b3db93b3f61728e698e4d"},"schema_version":"1.0"},"canonical_sha256":"7421a87ea589676ec794f09c3f4795e02aaf8a5bccf424ed313fbb3073b879c4","source":{"kind":"arxiv","id":"2506.13971","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.13971","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"arxiv_version","alias_value":"2506.13971v1","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.13971","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_12","alias_value":"OQQ2Q7VFRFTW","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_16","alias_value":"OQQ2Q7VFRFTW5R4U","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_8","alias_value":"OQQ2Q7VF","created_at":"2026-07-05T11:55:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:OQQ2Q7VFRFTW5R4U6COD6R4V4A","target":"record","payload":{"canonical_record":{"source":{"id":"2506.13971","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2025-06-01T01:09:08Z","cross_cats_sorted":["cs.CL","cs.HC","cs.LG","cs.MM"],"title_canon_sha256":"348cedcd12c772280c3075f73fa7a5aa205a45123ce52f1b26abfaf5ae550748","abstract_canon_sha256":"f03d7621c2a7f31c19ab906f1596d7ef884e4c57905b3db93b3f61728e698e4d"},"schema_version":"1.0"},"canonical_sha256":"7421a87ea589676ec794f09c3f4795e02aaf8a5bccf424ed313fbb3073b879c4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:55:40.797854Z","signature_b64":"WbpvblPNsyg+nr3Rm4MLi1M4TqmY+/YNOLpr+WAuLy6CkQqPBID82HTEKpGwV/hSNOoEWONvJgkSkofvlMAyCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7421a87ea589676ec794f09c3f4795e02aaf8a5bccf424ed313fbb3073b879c4","last_reissued_at":"2026-07-05T11:55:40.797386Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:55:40.797386Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.13971","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":"2026-07-05T11:55:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Dqw0yR03btiPPvm38GSZsQ0qKcF1xCTb/KucTczAqCBp/DMtZ0VbwjhvVkP1Eu2nXNP/5QmoWbANFCrEDdHwCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T07:53:26.180677Z"},"content_sha256":"c4135d30d5de77cf6725d2a94ffbcd0cbe3455030d385da621fd45f27c2e3241","schema_version":"1.0","event_id":"sha256:c4135d30d5de77cf6725d2a94ffbcd0cbe3455030d385da621fd45f27c2e3241"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:OQQ2Q7VFRFTW5R4U6COD6R4V4A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multimodal Fusion with Semi-Supervised Learning Minimizes Annotation Quantity for Modeling Videoconference Conversation Experience","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.HC","cs.LG","cs.MM"],"primary_cat":"eess.AS","authors_text":"Andrew Chang, Chenkai Hu, David Poeppel, Dustin Freeman, Ji Qi, Kexin Zhang, Viswadruth Akkaraju, Zhuojian Wei","submitted_at":"2025-06-01T01:09:08Z","abstract_excerpt":"Group conversations over videoconferencing are a complex social behavior. However, the subjective moments of negative experience, where the conversation loses fluidity or enjoyment remain understudied. These moments are infrequent in naturalistic data, and thus training a supervised learning (SL) model requires costly manual data annotation. We applied semi-supervised learning (SSL) to leverage targeted labeled and unlabeled clips for training multimodal (audio, facial, text) deep features to predict non-fluid or unenjoyable moments in holdout videoconference sessions. The modality-fused co-tr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.13971","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/2506.13971/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":"2026-07-05T11:55:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vliS6QSI6J/63KdZSdZnWm9rn1IrLtIWVT/d8HjN10FY9di2k1vCzd3gxB3EOUEL48qdWIW/3o+lAXKbFwtmCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T07:53:26.181212Z"},"content_sha256":"85ebde6a2954b8661b30a8918f076fd4ce3c9f06a6e969ab43acc70d99fff035","schema_version":"1.0","event_id":"sha256:85ebde6a2954b8661b30a8918f076fd4ce3c9f06a6e969ab43acc70d99fff035"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OQQ2Q7VFRFTW5R4U6COD6R4V4A/bundle.json","state_url":"https://pith.science/pith/OQQ2Q7VFRFTW5R4U6COD6R4V4A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OQQ2Q7VFRFTW5R4U6COD6R4V4A/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":"2026-08-09T07:53:26Z","links":{"resolver":"https://pith.science/pith/OQQ2Q7VFRFTW5R4U6COD6R4V4A","bundle":"https://pith.science/pith/OQQ2Q7VFRFTW5R4U6COD6R4V4A/bundle.json","state":"https://pith.science/pith/OQQ2Q7VFRFTW5R4U6COD6R4V4A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OQQ2Q7VFRFTW5R4U6COD6R4V4A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:OQQ2Q7VFRFTW5R4U6COD6R4V4A","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":"f03d7621c2a7f31c19ab906f1596d7ef884e4c57905b3db93b3f61728e698e4d","cross_cats_sorted":["cs.CL","cs.HC","cs.LG","cs.MM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2025-06-01T01:09:08Z","title_canon_sha256":"348cedcd12c772280c3075f73fa7a5aa205a45123ce52f1b26abfaf5ae550748"},"schema_version":"1.0","source":{"id":"2506.13971","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.13971","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"arxiv_version","alias_value":"2506.13971v1","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.13971","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_12","alias_value":"OQQ2Q7VFRFTW","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_16","alias_value":"OQQ2Q7VFRFTW5R4U","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_8","alias_value":"OQQ2Q7VF","created_at":"2026-07-05T11:55:40Z"}],"graph_snapshots":[{"event_id":"sha256:85ebde6a2954b8661b30a8918f076fd4ce3c9f06a6e969ab43acc70d99fff035","target":"graph","created_at":"2026-07-05T11:55:40Z","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/2506.13971/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Group conversations over videoconferencing are a complex social behavior. However, the subjective moments of negative experience, where the conversation loses fluidity or enjoyment remain understudied. These moments are infrequent in naturalistic data, and thus training a supervised learning (SL) model requires costly manual data annotation. We applied semi-supervised learning (SSL) to leverage targeted labeled and unlabeled clips for training multimodal (audio, facial, text) deep features to predict non-fluid or unenjoyable moments in holdout videoconference sessions. The modality-fused co-tr","authors_text":"Andrew Chang, Chenkai Hu, David Poeppel, Dustin Freeman, Ji Qi, Kexin Zhang, Viswadruth Akkaraju, Zhuojian Wei","cross_cats":["cs.CL","cs.HC","cs.LG","cs.MM"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2025-06-01T01:09:08Z","title":"Multimodal Fusion with Semi-Supervised Learning Minimizes Annotation Quantity for Modeling Videoconference Conversation Experience"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.13971","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:c4135d30d5de77cf6725d2a94ffbcd0cbe3455030d385da621fd45f27c2e3241","target":"record","created_at":"2026-07-05T11:55:40Z","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":"f03d7621c2a7f31c19ab906f1596d7ef884e4c57905b3db93b3f61728e698e4d","cross_cats_sorted":["cs.CL","cs.HC","cs.LG","cs.MM"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2025-06-01T01:09:08Z","title_canon_sha256":"348cedcd12c772280c3075f73fa7a5aa205a45123ce52f1b26abfaf5ae550748"},"schema_version":"1.0","source":{"id":"2506.13971","kind":"arxiv","version":1}},"canonical_sha256":"7421a87ea589676ec794f09c3f4795e02aaf8a5bccf424ed313fbb3073b879c4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7421a87ea589676ec794f09c3f4795e02aaf8a5bccf424ed313fbb3073b879c4","first_computed_at":"2026-07-05T11:55:40.797386Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:55:40.797386Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WbpvblPNsyg+nr3Rm4MLi1M4TqmY+/YNOLpr+WAuLy6CkQqPBID82HTEKpGwV/hSNOoEWONvJgkSkofvlMAyCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:55:40.797854Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.13971","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c4135d30d5de77cf6725d2a94ffbcd0cbe3455030d385da621fd45f27c2e3241","sha256:85ebde6a2954b8661b30a8918f076fd4ce3c9f06a6e969ab43acc70d99fff035"],"state_sha256":"788f701de89d67863abaeace2dc65f6c3e778aabb6f71e91840fce5bfc274267"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mqOfgjtn5C8LgTjNVjTYawpym/YLsLqsaGGGhYucjyW2pze025abrxXMmwC/9fy9t0iAx609B4cRxbMp1Bo1DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T07:53:26.186453Z","bundle_sha256":"ed0b041e50127172481a769e674494ab7efbea7f7ea38787a9fcad2890ad4cc7"}}