{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:XVITKUSGPL6WPWXDOEZLWIXQCF","short_pith_number":"pith:XVITKUSG","canonical_record":{"source":{"id":"2606.01856","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2026-06-01T08:07:09Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"6fbdf76a018dfae487f8274b346c5231b4452313e27d0195189e7bb5837c689a","abstract_canon_sha256":"0f72947678f7ec209e4df2b494f5aacd53ca7be8f6f8273540d336df09eebb6a"},"schema_version":"1.0"},"canonical_sha256":"bd513552467afd67dae37132bb22f0115f965ae48722b331342f397957cc28d6","source":{"kind":"arxiv","id":"2606.01856","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.01856","created_at":"2026-06-02T02:04:58Z"},{"alias_kind":"arxiv_version","alias_value":"2606.01856v1","created_at":"2026-06-02T02:04:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.01856","created_at":"2026-06-02T02:04:58Z"},{"alias_kind":"pith_short_12","alias_value":"XVITKUSGPL6W","created_at":"2026-06-02T02:04:58Z"},{"alias_kind":"pith_short_16","alias_value":"XVITKUSGPL6WPWXD","created_at":"2026-06-02T02:04:58Z"},{"alias_kind":"pith_short_8","alias_value":"XVITKUSG","created_at":"2026-06-02T02:04:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:XVITKUSGPL6WPWXDOEZLWIXQCF","target":"record","payload":{"canonical_record":{"source":{"id":"2606.01856","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2026-06-01T08:07:09Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"6fbdf76a018dfae487f8274b346c5231b4452313e27d0195189e7bb5837c689a","abstract_canon_sha256":"0f72947678f7ec209e4df2b494f5aacd53ca7be8f6f8273540d336df09eebb6a"},"schema_version":"1.0"},"canonical_sha256":"bd513552467afd67dae37132bb22f0115f965ae48722b331342f397957cc28d6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-02T02:04:58.786152Z","signature_b64":"3K9MQXQqs1zvSRj2tFLrDNbI64fRgUney44ZKX0W4rcKGfJ8iEdgC3m71gLIeZk7FfvGXvvAd9ppq8wSX9aOBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bd513552467afd67dae37132bb22f0115f965ae48722b331342f397957cc28d6","last_reissued_at":"2026-06-02T02:04:58.785740Z","signature_status":"signed_v1","first_computed_at":"2026-06-02T02:04:58.785740Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.01856","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":"2026-06-02T02:04:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zvVOMU2dU+r+ivdI2vKasJ9XXGK6u7MbwbXBMurd13kcaMQ9sV9GiLgLIn32lQ4vWPdhQ4nMJrGMnwYiLTqpAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T20:25:30.541232Z"},"content_sha256":"025dbbc7dcacfef00a13d9b480ee574b52a577b5c1c74c8543d0acf9f01578d0","schema_version":"1.0","event_id":"sha256:025dbbc7dcacfef00a13d9b480ee574b52a577b5c1c74c8543d0acf9f01578d0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:XVITKUSGPL6WPWXDOEZLWIXQCF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Boosting Multimodal Federated Learning via Chained Modality Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.DC","authors_text":"Changsheng Xu, Fan Qi, Shuai Li, Xiaoshan Yang, Zixin Zhang","submitted_at":"2026-06-01T08:07:09Z","abstract_excerpt":"Multimodal Federated Learning (MMFL) enables privacy-preserving collaborative learning across decentralized clients with heterogeneous data and modality availability. However, most existing MMFL methods cast multimodal training as a joint optimization problem, overlooking a key bottleneck: modality competition, where dominant modalities suppress weaker ones and lead to suboptimal global models. To address this, we propose FedMChain, a balanced MMFL framework that structures federated multimodal training as a chain of modality-wise phases. This phase-wise design gives each modality a dedicated "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.01856","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/2606.01856/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":"2026-06-02T02:04:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YJ+4mWjLd03XHa0zf63mkIg2v/ixcYZWqUqlA+Mk9NdqUpAB8NrTGOrYTeEkhhCCbFMkgc3JJB2YRMayavWDBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T20:25:30.541641Z"},"content_sha256":"04e7acbfc7fff79f0d4f787dbb0fe1c196c2f371fc15775b7b322af3215f1019","schema_version":"1.0","event_id":"sha256:04e7acbfc7fff79f0d4f787dbb0fe1c196c2f371fc15775b7b322af3215f1019"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XVITKUSGPL6WPWXDOEZLWIXQCF/bundle.json","state_url":"https://pith.science/pith/XVITKUSGPL6WPWXDOEZLWIXQCF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XVITKUSGPL6WPWXDOEZLWIXQCF/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":"2026-06-04T20:25:30Z","links":{"resolver":"https://pith.science/pith/XVITKUSGPL6WPWXDOEZLWIXQCF","bundle":"https://pith.science/pith/XVITKUSGPL6WPWXDOEZLWIXQCF/bundle.json","state":"https://pith.science/pith/XVITKUSGPL6WPWXDOEZLWIXQCF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XVITKUSGPL6WPWXDOEZLWIXQCF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:XVITKUSGPL6WPWXDOEZLWIXQCF","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":"0f72947678f7ec209e4df2b494f5aacd53ca7be8f6f8273540d336df09eebb6a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2026-06-01T08:07:09Z","title_canon_sha256":"6fbdf76a018dfae487f8274b346c5231b4452313e27d0195189e7bb5837c689a"},"schema_version":"1.0","source":{"id":"2606.01856","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.01856","created_at":"2026-06-02T02:04:58Z"},{"alias_kind":"arxiv_version","alias_value":"2606.01856v1","created_at":"2026-06-02T02:04:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.01856","created_at":"2026-06-02T02:04:58Z"},{"alias_kind":"pith_short_12","alias_value":"XVITKUSGPL6W","created_at":"2026-06-02T02:04:58Z"},{"alias_kind":"pith_short_16","alias_value":"XVITKUSGPL6WPWXD","created_at":"2026-06-02T02:04:58Z"},{"alias_kind":"pith_short_8","alias_value":"XVITKUSG","created_at":"2026-06-02T02:04:58Z"}],"graph_snapshots":[{"event_id":"sha256:04e7acbfc7fff79f0d4f787dbb0fe1c196c2f371fc15775b7b322af3215f1019","target":"graph","created_at":"2026-06-02T02:04:58Z","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/2606.01856/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multimodal Federated Learning (MMFL) enables privacy-preserving collaborative learning across decentralized clients with heterogeneous data and modality availability. However, most existing MMFL methods cast multimodal training as a joint optimization problem, overlooking a key bottleneck: modality competition, where dominant modalities suppress weaker ones and lead to suboptimal global models. To address this, we propose FedMChain, a balanced MMFL framework that structures federated multimodal training as a chain of modality-wise phases. This phase-wise design gives each modality a dedicated ","authors_text":"Changsheng Xu, Fan Qi, Shuai Li, Xiaoshan Yang, Zixin Zhang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2026-06-01T08:07:09Z","title":"Boosting Multimodal Federated Learning via Chained Modality Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.01856","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":"sha256:025dbbc7dcacfef00a13d9b480ee574b52a577b5c1c74c8543d0acf9f01578d0","target":"record","created_at":"2026-06-02T02:04:58Z","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":"0f72947678f7ec209e4df2b494f5aacd53ca7be8f6f8273540d336df09eebb6a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2026-06-01T08:07:09Z","title_canon_sha256":"6fbdf76a018dfae487f8274b346c5231b4452313e27d0195189e7bb5837c689a"},"schema_version":"1.0","source":{"id":"2606.01856","kind":"arxiv","version":1}},"canonical_sha256":"bd513552467afd67dae37132bb22f0115f965ae48722b331342f397957cc28d6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bd513552467afd67dae37132bb22f0115f965ae48722b331342f397957cc28d6","first_computed_at":"2026-06-02T02:04:58.785740Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-02T02:04:58.785740Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3K9MQXQqs1zvSRj2tFLrDNbI64fRgUney44ZKX0W4rcKGfJ8iEdgC3m71gLIeZk7FfvGXvvAd9ppq8wSX9aOBQ==","signature_status":"signed_v1","signed_at":"2026-06-02T02:04:58.786152Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.01856","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:025dbbc7dcacfef00a13d9b480ee574b52a577b5c1c74c8543d0acf9f01578d0","sha256:04e7acbfc7fff79f0d4f787dbb0fe1c196c2f371fc15775b7b322af3215f1019"],"state_sha256":"dabc6335d0a8ded50d0ad8ab5d68abc5cd1a15efb4de3c50f73d08f315402b49"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZHuC28BfmRTFWBUrEBZOKyUanHeHvxM67hLBfVfV84f+bSh9X/yzazSHqACcf/b7lqLXdAudcdAB4MXysXCZBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T20:25:30.543848Z","bundle_sha256":"345b03cb1d2077f0c409a971e67e08ba68cd0e5c830b8d49f1e3d907c10d2d7c"}}