{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:AQ7RLOK7HPY2FU7JIMTUU5UNAN","short_pith_number":"pith:AQ7RLOK7","canonical_record":{"source":{"id":"2305.11414","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-19T03:51:59Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"032c19fa2fe87f794087c80d4964db5889de403a23978baee6bc3a9f1113db72","abstract_canon_sha256":"341d23891456361fc13871615221e454259cab83da160197f2d78361b5078268"},"schema_version":"1.0"},"canonical_sha256":"043f15b95f3bf1a2d3e943274a768d035f02e5ab8d1b1066f73f8d9c19479e0b","source":{"kind":"arxiv","id":"2305.11414","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.11414","created_at":"2026-07-05T07:58:20Z"},{"alias_kind":"arxiv_version","alias_value":"2305.11414v3","created_at":"2026-07-05T07:58:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.11414","created_at":"2026-07-05T07:58:20Z"},{"alias_kind":"pith_short_12","alias_value":"AQ7RLOK7HPY2","created_at":"2026-07-05T07:58:20Z"},{"alias_kind":"pith_short_16","alias_value":"AQ7RLOK7HPY2FU7J","created_at":"2026-07-05T07:58:20Z"},{"alias_kind":"pith_short_8","alias_value":"AQ7RLOK7","created_at":"2026-07-05T07:58:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:AQ7RLOK7HPY2FU7JIMTUU5UNAN","target":"record","payload":{"canonical_record":{"source":{"id":"2305.11414","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-19T03:51:59Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"032c19fa2fe87f794087c80d4964db5889de403a23978baee6bc3a9f1113db72","abstract_canon_sha256":"341d23891456361fc13871615221e454259cab83da160197f2d78361b5078268"},"schema_version":"1.0"},"canonical_sha256":"043f15b95f3bf1a2d3e943274a768d035f02e5ab8d1b1066f73f8d9c19479e0b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:58:20.169974Z","signature_b64":"M0N87zp7/b8wc7fTMI8ZYmSALp84RrqNfQvdkNg50ee5TOD7ChjrjJUarZ+3hgSC4D9JyluDyKimQgGDYNqjAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"043f15b95f3bf1a2d3e943274a768d035f02e5ab8d1b1066f73f8d9c19479e0b","last_reissued_at":"2026-07-05T07:58:20.169629Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:58:20.169629Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.11414","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":"2026-07-05T07:58:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TEQ2FfguVQp/JKOMrVlgxJyIbIqOGekjeb3nVHjmrV+dx3ESh5JM1wIWPGiXjO3qOx0W6U03NcqNnVyfQQz3DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T03:40:31.554528Z"},"content_sha256":"a1423584255448e0312316e99b62748eb8c13a1fc3844bc3affe43acf285dfed","schema_version":"1.0","event_id":"sha256:a1423584255448e0312316e99b62748eb8c13a1fc3844bc3affe43acf285dfed"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:AQ7RLOK7HPY2FU7JIMTUU5UNAN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CR"],"primary_cat":"cs.LG","authors_text":"Ali Jannesari, J. Pablo Mu\\~noz, Sixing Yu","submitted_at":"2023-05-19T03:51:59Z","abstract_excerpt":"Foundation Models (FMs), such as LLaMA, BERT, GPT, ViT, and CLIP, have demonstrated remarkable success in a wide range of applications, driven by their ability to leverage vast amounts of data for pre-training. However, optimizing FMs often requires access to sensitive data, raising privacy concerns and limiting their applicability in many domains. In this paper, we propose the Federated Foundation Models (FFMs) paradigm, which combines the benefits of FMs and Federated Learning (FL) to enable privacy-preserving and collaborative learning across multiple end-users. We discuss the potential ben"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.11414","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/2305.11414/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":"2026-07-05T07:58:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b0/CbLlKxn4JXmg+R42pevjNKVOB/J6unjW4Bk6Z2Cz6g2EZRlzcgtdCkvjOBqAFKHPAAJOjf/Kdds35vW/2Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T03:40:31.555458Z"},"content_sha256":"cb750d073be9c62a6b1f94b64d5915d7265d6afbe95dfac89c38502910af020e","schema_version":"1.0","event_id":"sha256:cb750d073be9c62a6b1f94b64d5915d7265d6afbe95dfac89c38502910af020e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AQ7RLOK7HPY2FU7JIMTUU5UNAN/bundle.json","state_url":"https://pith.science/pith/AQ7RLOK7HPY2FU7JIMTUU5UNAN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AQ7RLOK7HPY2FU7JIMTUU5UNAN/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":"2026-08-09T03:40:31Z","links":{"resolver":"https://pith.science/pith/AQ7RLOK7HPY2FU7JIMTUU5UNAN","bundle":"https://pith.science/pith/AQ7RLOK7HPY2FU7JIMTUU5UNAN/bundle.json","state":"https://pith.science/pith/AQ7RLOK7HPY2FU7JIMTUU5UNAN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AQ7RLOK7HPY2FU7JIMTUU5UNAN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:AQ7RLOK7HPY2FU7JIMTUU5UNAN","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":"341d23891456361fc13871615221e454259cab83da160197f2d78361b5078268","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-19T03:51:59Z","title_canon_sha256":"032c19fa2fe87f794087c80d4964db5889de403a23978baee6bc3a9f1113db72"},"schema_version":"1.0","source":{"id":"2305.11414","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.11414","created_at":"2026-07-05T07:58:20Z"},{"alias_kind":"arxiv_version","alias_value":"2305.11414v3","created_at":"2026-07-05T07:58:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.11414","created_at":"2026-07-05T07:58:20Z"},{"alias_kind":"pith_short_12","alias_value":"AQ7RLOK7HPY2","created_at":"2026-07-05T07:58:20Z"},{"alias_kind":"pith_short_16","alias_value":"AQ7RLOK7HPY2FU7J","created_at":"2026-07-05T07:58:20Z"},{"alias_kind":"pith_short_8","alias_value":"AQ7RLOK7","created_at":"2026-07-05T07:58:20Z"}],"graph_snapshots":[{"event_id":"sha256:cb750d073be9c62a6b1f94b64d5915d7265d6afbe95dfac89c38502910af020e","target":"graph","created_at":"2026-07-05T07:58:20Z","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/2305.11414/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Foundation Models (FMs), such as LLaMA, BERT, GPT, ViT, and CLIP, have demonstrated remarkable success in a wide range of applications, driven by their ability to leverage vast amounts of data for pre-training. However, optimizing FMs often requires access to sensitive data, raising privacy concerns and limiting their applicability in many domains. In this paper, we propose the Federated Foundation Models (FFMs) paradigm, which combines the benefits of FMs and Federated Learning (FL) to enable privacy-preserving and collaborative learning across multiple end-users. We discuss the potential ben","authors_text":"Ali Jannesari, J. Pablo Mu\\~noz, Sixing Yu","cross_cats":["cs.AI","cs.CR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-19T03:51:59Z","title":"Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.11414","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:a1423584255448e0312316e99b62748eb8c13a1fc3844bc3affe43acf285dfed","target":"record","created_at":"2026-07-05T07:58:20Z","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":"341d23891456361fc13871615221e454259cab83da160197f2d78361b5078268","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-19T03:51:59Z","title_canon_sha256":"032c19fa2fe87f794087c80d4964db5889de403a23978baee6bc3a9f1113db72"},"schema_version":"1.0","source":{"id":"2305.11414","kind":"arxiv","version":3}},"canonical_sha256":"043f15b95f3bf1a2d3e943274a768d035f02e5ab8d1b1066f73f8d9c19479e0b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"043f15b95f3bf1a2d3e943274a768d035f02e5ab8d1b1066f73f8d9c19479e0b","first_computed_at":"2026-07-05T07:58:20.169629Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:58:20.169629Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"M0N87zp7/b8wc7fTMI8ZYmSALp84RrqNfQvdkNg50ee5TOD7ChjrjJUarZ+3hgSC4D9JyluDyKimQgGDYNqjAw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:58:20.169974Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.11414","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a1423584255448e0312316e99b62748eb8c13a1fc3844bc3affe43acf285dfed","sha256:cb750d073be9c62a6b1f94b64d5915d7265d6afbe95dfac89c38502910af020e"],"state_sha256":"91d21dac91a2a4b2969687bfe5eefc1b932d7083c501e89d1c412fde58fb12bf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mmDtrnShoVt4aIIwIAvdSdUgPdGRpdqp+KmKy5ySVClYK3koqFJL0mgTV9V9g2oaSBbUhyKUTa8WfiTCQQwsDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T03:40:31.561055Z","bundle_sha256":"025c25c84be5a652546b4d6b61a7ee8138fbb04d625168b53fc3d622a378e123"}}