{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:4TZLC5MYJWNIMP7KUF3E4PYSF7","short_pith_number":"pith:4TZLC5MY","canonical_record":{"source":{"id":"2505.06911","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-11T09:12:36Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"bd6d51ce0e695f7b9eb1bce52e7bba8704aa9235e419e125447e1289fe3156bb","abstract_canon_sha256":"7dffbdbdb79bde8c15836d6fcd1aea4628de639a70c09d55b71f0d4de5abd7c2"},"schema_version":"1.0"},"canonical_sha256":"e4f2b175984d9a863feaa1764e3f122fdd3a9ec85dceb03c554474ad10806a5c","source":{"kind":"arxiv","id":"2505.06911","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.06911","created_at":"2026-07-05T11:56:56Z"},{"alias_kind":"arxiv_version","alias_value":"2505.06911v3","created_at":"2026-07-05T11:56:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.06911","created_at":"2026-07-05T11:56:56Z"},{"alias_kind":"pith_short_12","alias_value":"4TZLC5MYJWNI","created_at":"2026-07-05T11:56:56Z"},{"alias_kind":"pith_short_16","alias_value":"4TZLC5MYJWNIMP7K","created_at":"2026-07-05T11:56:56Z"},{"alias_kind":"pith_short_8","alias_value":"4TZLC5MY","created_at":"2026-07-05T11:56:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:4TZLC5MYJWNIMP7KUF3E4PYSF7","target":"record","payload":{"canonical_record":{"source":{"id":"2505.06911","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-11T09:12:36Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"bd6d51ce0e695f7b9eb1bce52e7bba8704aa9235e419e125447e1289fe3156bb","abstract_canon_sha256":"7dffbdbdb79bde8c15836d6fcd1aea4628de639a70c09d55b71f0d4de5abd7c2"},"schema_version":"1.0"},"canonical_sha256":"e4f2b175984d9a863feaa1764e3f122fdd3a9ec85dceb03c554474ad10806a5c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:56:56.907306Z","signature_b64":"8xEeS19U+O0M0C+Tuce1SrxMXd+Y98+o4ZKmgRIHIowDaDr49RLTi2nkHJPUScmoBOyFm6ZYGHFQ0QMRPLSdBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e4f2b175984d9a863feaa1764e3f122fdd3a9ec85dceb03c554474ad10806a5c","last_reissued_at":"2026-07-05T11:56:56.906827Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:56:56.906827Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.06911","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":"2026-07-05T11:56:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dLHZi83Zd/PvNoFZMV0tvqNoFiKpbnX1hj/PqdgKWCFQcfwsIcpD3OSEIlz4Z/3jlxlH0og3YwFZ7E5gJu3UDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T21:00:11.886990Z"},"content_sha256":"d73690a73d93c15f38b849445d77682efb6ea2acf3ddabb5406c24dfb084f464","schema_version":"1.0","event_id":"sha256:d73690a73d93c15f38b849445d77682efb6ea2acf3ddabb5406c24dfb084f464"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:4TZLC5MYJWNIMP7KUF3E4PYSF7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MMiC: Mitigating Modality Incompleteness in Clustered Federated Learning","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Ali Shakeri, Lina Yao, Lishan Yang, Quan Z. Sheng, Wei Emma Zhang, Weitong Chen","submitted_at":"2025-05-11T09:12:36Z","abstract_excerpt":"In the era of big data, data mining has become indispensable for uncovering hidden patterns and insights from vast and complex datasets. The integration of multimodal data sources further enhances its potential. Multimodal Federated Learning (MFL) is a distributed approach that enhances the efficiency and quality of multimodal learning, ensuring collaborative work and privacy protection. However, missing modalities pose a significant challenge in MFL, often due to data quality issues or privacy policies across the clients. In this work, we present MMiC, a framework for Mitigating Modality inco"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.06911","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/2505.06911/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":"2026-07-05T11:56:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rigjLHvnsq5wdcscDetuJPcK6mh2KhuZpPGSfESqDxTptvnHfCbfswJRG/qRCxRytt0Zh/sPxC/xp2bRVmfzAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T21:00:11.887511Z"},"content_sha256":"c49f3b739711af90e85c14e089d5f99df8d7a27a4fca6ba2405c051a55e66b52","schema_version":"1.0","event_id":"sha256:c49f3b739711af90e85c14e089d5f99df8d7a27a4fca6ba2405c051a55e66b52"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4TZLC5MYJWNIMP7KUF3E4PYSF7/bundle.json","state_url":"https://pith.science/pith/4TZLC5MYJWNIMP7KUF3E4PYSF7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4TZLC5MYJWNIMP7KUF3E4PYSF7/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":"2026-08-20T21:00:11Z","links":{"resolver":"https://pith.science/pith/4TZLC5MYJWNIMP7KUF3E4PYSF7","bundle":"https://pith.science/pith/4TZLC5MYJWNIMP7KUF3E4PYSF7/bundle.json","state":"https://pith.science/pith/4TZLC5MYJWNIMP7KUF3E4PYSF7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4TZLC5MYJWNIMP7KUF3E4PYSF7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4TZLC5MYJWNIMP7KUF3E4PYSF7","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":"7dffbdbdb79bde8c15836d6fcd1aea4628de639a70c09d55b71f0d4de5abd7c2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-11T09:12:36Z","title_canon_sha256":"bd6d51ce0e695f7b9eb1bce52e7bba8704aa9235e419e125447e1289fe3156bb"},"schema_version":"1.0","source":{"id":"2505.06911","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.06911","created_at":"2026-07-05T11:56:56Z"},{"alias_kind":"arxiv_version","alias_value":"2505.06911v3","created_at":"2026-07-05T11:56:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.06911","created_at":"2026-07-05T11:56:56Z"},{"alias_kind":"pith_short_12","alias_value":"4TZLC5MYJWNI","created_at":"2026-07-05T11:56:56Z"},{"alias_kind":"pith_short_16","alias_value":"4TZLC5MYJWNIMP7K","created_at":"2026-07-05T11:56:56Z"},{"alias_kind":"pith_short_8","alias_value":"4TZLC5MY","created_at":"2026-07-05T11:56:56Z"}],"graph_snapshots":[{"event_id":"sha256:c49f3b739711af90e85c14e089d5f99df8d7a27a4fca6ba2405c051a55e66b52","target":"graph","created_at":"2026-07-05T11:56:56Z","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/2505.06911/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In the era of big data, data mining has become indispensable for uncovering hidden patterns and insights from vast and complex datasets. The integration of multimodal data sources further enhances its potential. Multimodal Federated Learning (MFL) is a distributed approach that enhances the efficiency and quality of multimodal learning, ensuring collaborative work and privacy protection. However, missing modalities pose a significant challenge in MFL, often due to data quality issues or privacy policies across the clients. In this work, we present MMiC, a framework for Mitigating Modality inco","authors_text":"Ali Shakeri, Lina Yao, Lishan Yang, Quan Z. Sheng, Wei Emma Zhang, Weitong Chen","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-11T09:12:36Z","title":"MMiC: Mitigating Modality Incompleteness in Clustered Federated Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.06911","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:d73690a73d93c15f38b849445d77682efb6ea2acf3ddabb5406c24dfb084f464","target":"record","created_at":"2026-07-05T11:56:56Z","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":"7dffbdbdb79bde8c15836d6fcd1aea4628de639a70c09d55b71f0d4de5abd7c2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-11T09:12:36Z","title_canon_sha256":"bd6d51ce0e695f7b9eb1bce52e7bba8704aa9235e419e125447e1289fe3156bb"},"schema_version":"1.0","source":{"id":"2505.06911","kind":"arxiv","version":3}},"canonical_sha256":"e4f2b175984d9a863feaa1764e3f122fdd3a9ec85dceb03c554474ad10806a5c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e4f2b175984d9a863feaa1764e3f122fdd3a9ec85dceb03c554474ad10806a5c","first_computed_at":"2026-07-05T11:56:56.906827Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:56:56.906827Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8xEeS19U+O0M0C+Tuce1SrxMXd+Y98+o4ZKmgRIHIowDaDr49RLTi2nkHJPUScmoBOyFm6ZYGHFQ0QMRPLSdBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:56:56.907306Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.06911","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d73690a73d93c15f38b849445d77682efb6ea2acf3ddabb5406c24dfb084f464","sha256:c49f3b739711af90e85c14e089d5f99df8d7a27a4fca6ba2405c051a55e66b52"],"state_sha256":"e67dcc09447b1bef263a9356b2125cfb4ddab7105cc4cfe8451df2c2d62b5610"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g/D46TITnvhfp1H0MDqwMPR+uItXsnQT3AR2osy2gybSfOQWC17rOmnxGdXuvZJPaTy2TBJFRoNVzo9i4N+qBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T21:00:11.893039Z","bundle_sha256":"d56880283e3e1e960b6f74eb1a0804c0bd624fe8d462b01a9396c5c78b23a768"}}