{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:MSUT2FXCDCWIFEHHNAPO57IJAL","short_pith_number":"pith:MSUT2FXC","canonical_record":{"source":{"id":"2302.09042","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-17T18:18:22Z","cross_cats_sorted":["cs.AI","cs.DC"],"title_canon_sha256":"799dcadf4715312cd17b48d16e8069d1b7539f60f54ec1188e6ad72f096d97f7","abstract_canon_sha256":"b3da6b15260fc93e4e83cfebdd5f88421ee3526eb0ee45ed652d2a30d7d53a17"},"schema_version":"1.0"},"canonical_sha256":"64a93d16e218ac8290e7681eeefd0902ce38bc34c55e3bcfb5651e9d23464fa7","source":{"kind":"arxiv","id":"2302.09042","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.09042","created_at":"2026-07-05T05:44:53Z"},{"alias_kind":"arxiv_version","alias_value":"2302.09042v2","created_at":"2026-07-05T05:44:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.09042","created_at":"2026-07-05T05:44:53Z"},{"alias_kind":"pith_short_12","alias_value":"MSUT2FXCDCWI","created_at":"2026-07-05T05:44:53Z"},{"alias_kind":"pith_short_16","alias_value":"MSUT2FXCDCWIFEHH","created_at":"2026-07-05T05:44:53Z"},{"alias_kind":"pith_short_8","alias_value":"MSUT2FXC","created_at":"2026-07-05T05:44:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:MSUT2FXCDCWIFEHHNAPO57IJAL","target":"record","payload":{"canonical_record":{"source":{"id":"2302.09042","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-17T18:18:22Z","cross_cats_sorted":["cs.AI","cs.DC"],"title_canon_sha256":"799dcadf4715312cd17b48d16e8069d1b7539f60f54ec1188e6ad72f096d97f7","abstract_canon_sha256":"b3da6b15260fc93e4e83cfebdd5f88421ee3526eb0ee45ed652d2a30d7d53a17"},"schema_version":"1.0"},"canonical_sha256":"64a93d16e218ac8290e7681eeefd0902ce38bc34c55e3bcfb5651e9d23464fa7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:44:53.256231Z","signature_b64":"nNt+ZhRIbm/lJ5szJ/h+Nn6bQIW07EqrpszW5lKv4+swQi0w49VikgZEYYuD4doRx5aFM88vcEfKwQbkvezMCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"64a93d16e218ac8290e7681eeefd0902ce38bc34c55e3bcfb5651e9d23464fa7","last_reissued_at":"2026-07-05T05:44:53.255808Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:44:53.255808Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2302.09042","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:44:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WxtTdNVV35C2PHBK517mrkbL4L6zp2hhINRiTq7acxj4t6/QOd2l+NSvPqtFyIau6ZfipeWx2yLBCOZCxKwdAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T03:00:08.563799Z"},"content_sha256":"1b64017c6930a622f9d665b4020dbaae906fe172011d842e4bea7cfff4682b9d","schema_version":"1.0","event_id":"sha256:1b64017c6930a622f9d665b4020dbaae906fe172011d842e4bea7cfff4682b9d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:MSUT2FXCDCWIFEHHNAPO57IJAL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Privately Customizing Prefinetuning to Better Match User Data in Federated Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.DC"],"primary_cat":"cs.LG","authors_text":"Akshat Shrivastava, Aleksandr Livshits, Charlie Hou, Daniel Lazar, Giulia Fanti, Hongyuan Zhan, Sid Wang","submitted_at":"2023-02-17T18:18:22Z","abstract_excerpt":"In Federated Learning (FL), accessing private client data incurs communication and privacy costs. As a result, FL deployments commonly prefinetune pretrained foundation models on a (large, possibly public) dataset that is held by the central server; they then FL-finetune the model on a private, federated dataset held by clients. Evaluating prefinetuning dataset quality reliably and privately is therefore of high importance. To this end, we propose FreD (Federated Private Fr\\'echet Distance) -- a privately computed distance between a prefinetuning dataset and federated datasets. Intuitively, it"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.09042","kind":"arxiv","version":2},"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/2302.09042/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":"2026-07-05T05:44:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N/rtJuqIQIGXI8kvdevQ6EKYnV71f/klZlvAZOaVJpTRqI2tkDemNOdGV0C7DsX9M+rE9qaLWhebZorBrqMKCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T03:00:08.564172Z"},"content_sha256":"f1f90e65cbdd3d2b1b96864de28e247c8cb856de221f82a6f72dad78907040e5","schema_version":"1.0","event_id":"sha256:f1f90e65cbdd3d2b1b96864de28e247c8cb856de221f82a6f72dad78907040e5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MSUT2FXCDCWIFEHHNAPO57IJAL/bundle.json","state_url":"https://pith.science/pith/MSUT2FXCDCWIFEHHNAPO57IJAL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MSUT2FXCDCWIFEHHNAPO57IJAL/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":"2026-08-13T03:00:08Z","links":{"resolver":"https://pith.science/pith/MSUT2FXCDCWIFEHHNAPO57IJAL","bundle":"https://pith.science/pith/MSUT2FXCDCWIFEHHNAPO57IJAL/bundle.json","state":"https://pith.science/pith/MSUT2FXCDCWIFEHHNAPO57IJAL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MSUT2FXCDCWIFEHHNAPO57IJAL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:MSUT2FXCDCWIFEHHNAPO57IJAL","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":"b3da6b15260fc93e4e83cfebdd5f88421ee3526eb0ee45ed652d2a30d7d53a17","cross_cats_sorted":["cs.AI","cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-17T18:18:22Z","title_canon_sha256":"799dcadf4715312cd17b48d16e8069d1b7539f60f54ec1188e6ad72f096d97f7"},"schema_version":"1.0","source":{"id":"2302.09042","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.09042","created_at":"2026-07-05T05:44:53Z"},{"alias_kind":"arxiv_version","alias_value":"2302.09042v2","created_at":"2026-07-05T05:44:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.09042","created_at":"2026-07-05T05:44:53Z"},{"alias_kind":"pith_short_12","alias_value":"MSUT2FXCDCWI","created_at":"2026-07-05T05:44:53Z"},{"alias_kind":"pith_short_16","alias_value":"MSUT2FXCDCWIFEHH","created_at":"2026-07-05T05:44:53Z"},{"alias_kind":"pith_short_8","alias_value":"MSUT2FXC","created_at":"2026-07-05T05:44:53Z"}],"graph_snapshots":[{"event_id":"sha256:f1f90e65cbdd3d2b1b96864de28e247c8cb856de221f82a6f72dad78907040e5","target":"graph","created_at":"2026-07-05T05:44:53Z","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/2302.09042/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In Federated Learning (FL), accessing private client data incurs communication and privacy costs. As a result, FL deployments commonly prefinetune pretrained foundation models on a (large, possibly public) dataset that is held by the central server; they then FL-finetune the model on a private, federated dataset held by clients. Evaluating prefinetuning dataset quality reliably and privately is therefore of high importance. To this end, we propose FreD (Federated Private Fr\\'echet Distance) -- a privately computed distance between a prefinetuning dataset and federated datasets. Intuitively, it","authors_text":"Akshat Shrivastava, Aleksandr Livshits, Charlie Hou, Daniel Lazar, Giulia Fanti, Hongyuan Zhan, Sid Wang","cross_cats":["cs.AI","cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-17T18:18:22Z","title":"Privately Customizing Prefinetuning to Better Match User Data in Federated Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.09042","kind":"arxiv","version":2},"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":"sha256:1b64017c6930a622f9d665b4020dbaae906fe172011d842e4bea7cfff4682b9d","target":"record","created_at":"2026-07-05T05:44:53Z","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":"b3da6b15260fc93e4e83cfebdd5f88421ee3526eb0ee45ed652d2a30d7d53a17","cross_cats_sorted":["cs.AI","cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-17T18:18:22Z","title_canon_sha256":"799dcadf4715312cd17b48d16e8069d1b7539f60f54ec1188e6ad72f096d97f7"},"schema_version":"1.0","source":{"id":"2302.09042","kind":"arxiv","version":2}},"canonical_sha256":"64a93d16e218ac8290e7681eeefd0902ce38bc34c55e3bcfb5651e9d23464fa7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"64a93d16e218ac8290e7681eeefd0902ce38bc34c55e3bcfb5651e9d23464fa7","first_computed_at":"2026-07-05T05:44:53.255808Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:44:53.255808Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nNt+ZhRIbm/lJ5szJ/h+Nn6bQIW07EqrpszW5lKv4+swQi0w49VikgZEYYuD4doRx5aFM88vcEfKwQbkvezMCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:44:53.256231Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.09042","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1b64017c6930a622f9d665b4020dbaae906fe172011d842e4bea7cfff4682b9d","sha256:f1f90e65cbdd3d2b1b96864de28e247c8cb856de221f82a6f72dad78907040e5"],"state_sha256":"66b44be9f391c24c8264e1369d2bf9d83c931a4af9126eb7dbb4e95bdb68212e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mGYS1zzaUkhLplz0A5hyfYky3gfV2PfW9/U2LLxG3J8y2mOmFzoE8wdsYNDeuxPbLAu1CAYrHkHn3fNn8hy0BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T03:00:08.566699Z","bundle_sha256":"78272a1e4f1d6fbb2399d8149a093e068ee5f484027f4b27981f39a07a2877d7"}}