{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:V6C3KYH5R2DHY4AIX2NXLIPOCJ","short_pith_number":"pith:V6C3KYH5","canonical_record":{"source":{"id":"2407.05268","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-07T05:46:01Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"ff964beee718c6e2a4547573c0d8b5859a8f89ef4e9e7864e867b53234e6b51b","abstract_canon_sha256":"dd97296abf5aa03700b2c36ec48e70c9b99385ffba76ef20a3dd8aa811daa23d"},"schema_version":"1.0"},"canonical_sha256":"af85b560fd8e867c7008be9b75a1ee126dfc0e8af6b4f26d139328f5b3e2fde1","source":{"kind":"arxiv","id":"2407.05268","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.05268","created_at":"2026-07-05T08:41:10Z"},{"alias_kind":"arxiv_version","alias_value":"2407.05268v1","created_at":"2026-07-05T08:41:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.05268","created_at":"2026-07-05T08:41:10Z"},{"alias_kind":"pith_short_12","alias_value":"V6C3KYH5R2DH","created_at":"2026-07-05T08:41:10Z"},{"alias_kind":"pith_short_16","alias_value":"V6C3KYH5R2DHY4AI","created_at":"2026-07-05T08:41:10Z"},{"alias_kind":"pith_short_8","alias_value":"V6C3KYH5","created_at":"2026-07-05T08:41:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:V6C3KYH5R2DHY4AIX2NXLIPOCJ","target":"record","payload":{"canonical_record":{"source":{"id":"2407.05268","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-07T05:46:01Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"ff964beee718c6e2a4547573c0d8b5859a8f89ef4e9e7864e867b53234e6b51b","abstract_canon_sha256":"dd97296abf5aa03700b2c36ec48e70c9b99385ffba76ef20a3dd8aa811daa23d"},"schema_version":"1.0"},"canonical_sha256":"af85b560fd8e867c7008be9b75a1ee126dfc0e8af6b4f26d139328f5b3e2fde1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:41:10.532603Z","signature_b64":"mT2cm2bTT5Tf38jzutjh8umO4vFFpwfsFTmOlCWRLUHrMJz9mbBqJXunkZvxr7Z5i5qkK/2avHxabtSAopKrAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"af85b560fd8e867c7008be9b75a1ee126dfc0e8af6b4f26d139328f5b3e2fde1","last_reissued_at":"2026-07-05T08:41:10.532167Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:41:10.532167Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.05268","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":"2026-07-05T08:41:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"btdlwSXR7VhGiUwepzS7UPwTEFsaozabzNQ5QQIcpGV1tf0ExNskw/A8Hyl33/+d6k1uDXqUP/rsvfD1zeLkAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T19:24:32.600810Z"},"content_sha256":"f1157bff5f2bbd8d7c516137f226d73f05272f4416c1815a37a81fd14a1e55bc","schema_version":"1.0","event_id":"sha256:f1157bff5f2bbd8d7c516137f226d73f05272f4416c1815a37a81fd14a1e55bc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:V6C3KYH5R2DHY4AIX2NXLIPOCJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Federated Knowledge Transfer Fine-tuning Large Server Model with Resource-Constrained IoT Clients","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Ahmed M. Abdelmoniem, Linlin You, Rui Liu, Shaoyuan Chen, Shuo Yu","submitted_at":"2024-07-07T05:46:01Z","abstract_excerpt":"The training of large models, involving fine-tuning, faces the scarcity of high-quality data. Compared to the solutions based on centralized data centers, updating large models in the Internet of Things (IoT) faces challenges in coordinating knowledge from distributed clients by using their private and heterogeneous data. To tackle such a challenge, we propose KOALA (Federated Knowledge Transfer Fine-tuning Large Server Model with Resource-Constrained IoT Clients) to impel the training of large models in IoT. Since the resources obtained by IoT clients are limited and restricted, it is infeasi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.05268","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/2407.05268/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":"2026-07-05T08:41:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eRNMIv7CW/8ZExG7UOuVWlO4gAMUQQHh1knTVHtA7U1DwrqK1Tii8qlvIjPN2a3nRBe2SnhLn+fzh7BlKGmdCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T19:24:32.601408Z"},"content_sha256":"ed1cb56580d43f3a6394f6b2645a87834d209373146b545638b2af3c835dc42d","schema_version":"1.0","event_id":"sha256:ed1cb56580d43f3a6394f6b2645a87834d209373146b545638b2af3c835dc42d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V6C3KYH5R2DHY4AIX2NXLIPOCJ/bundle.json","state_url":"https://pith.science/pith/V6C3KYH5R2DHY4AIX2NXLIPOCJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V6C3KYH5R2DHY4AIX2NXLIPOCJ/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":"2026-08-04T19:24:32Z","links":{"resolver":"https://pith.science/pith/V6C3KYH5R2DHY4AIX2NXLIPOCJ","bundle":"https://pith.science/pith/V6C3KYH5R2DHY4AIX2NXLIPOCJ/bundle.json","state":"https://pith.science/pith/V6C3KYH5R2DHY4AIX2NXLIPOCJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V6C3KYH5R2DHY4AIX2NXLIPOCJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:V6C3KYH5R2DHY4AIX2NXLIPOCJ","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":"dd97296abf5aa03700b2c36ec48e70c9b99385ffba76ef20a3dd8aa811daa23d","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-07T05:46:01Z","title_canon_sha256":"ff964beee718c6e2a4547573c0d8b5859a8f89ef4e9e7864e867b53234e6b51b"},"schema_version":"1.0","source":{"id":"2407.05268","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.05268","created_at":"2026-07-05T08:41:10Z"},{"alias_kind":"arxiv_version","alias_value":"2407.05268v1","created_at":"2026-07-05T08:41:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.05268","created_at":"2026-07-05T08:41:10Z"},{"alias_kind":"pith_short_12","alias_value":"V6C3KYH5R2DH","created_at":"2026-07-05T08:41:10Z"},{"alias_kind":"pith_short_16","alias_value":"V6C3KYH5R2DHY4AI","created_at":"2026-07-05T08:41:10Z"},{"alias_kind":"pith_short_8","alias_value":"V6C3KYH5","created_at":"2026-07-05T08:41:10Z"}],"graph_snapshots":[{"event_id":"sha256:ed1cb56580d43f3a6394f6b2645a87834d209373146b545638b2af3c835dc42d","target":"graph","created_at":"2026-07-05T08:41:10Z","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/2407.05268/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The training of large models, involving fine-tuning, faces the scarcity of high-quality data. Compared to the solutions based on centralized data centers, updating large models in the Internet of Things (IoT) faces challenges in coordinating knowledge from distributed clients by using their private and heterogeneous data. To tackle such a challenge, we propose KOALA (Federated Knowledge Transfer Fine-tuning Large Server Model with Resource-Constrained IoT Clients) to impel the training of large models in IoT. Since the resources obtained by IoT clients are limited and restricted, it is infeasi","authors_text":"Ahmed M. Abdelmoniem, Linlin You, Rui Liu, Shaoyuan Chen, Shuo Yu","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-07T05:46:01Z","title":"Federated Knowledge Transfer Fine-tuning Large Server Model with Resource-Constrained IoT Clients"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.05268","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:f1157bff5f2bbd8d7c516137f226d73f05272f4416c1815a37a81fd14a1e55bc","target":"record","created_at":"2026-07-05T08:41:10Z","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":"dd97296abf5aa03700b2c36ec48e70c9b99385ffba76ef20a3dd8aa811daa23d","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-07-07T05:46:01Z","title_canon_sha256":"ff964beee718c6e2a4547573c0d8b5859a8f89ef4e9e7864e867b53234e6b51b"},"schema_version":"1.0","source":{"id":"2407.05268","kind":"arxiv","version":1}},"canonical_sha256":"af85b560fd8e867c7008be9b75a1ee126dfc0e8af6b4f26d139328f5b3e2fde1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"af85b560fd8e867c7008be9b75a1ee126dfc0e8af6b4f26d139328f5b3e2fde1","first_computed_at":"2026-07-05T08:41:10.532167Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:41:10.532167Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mT2cm2bTT5Tf38jzutjh8umO4vFFpwfsFTmOlCWRLUHrMJz9mbBqJXunkZvxr7Z5i5qkK/2avHxabtSAopKrAw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:41:10.532603Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.05268","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f1157bff5f2bbd8d7c516137f226d73f05272f4416c1815a37a81fd14a1e55bc","sha256:ed1cb56580d43f3a6394f6b2645a87834d209373146b545638b2af3c835dc42d"],"state_sha256":"f6ef50fa1625156d5962599776bcd62c61acb0f7365ab18b4a77b38b03897482"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3U6woXI6t4TPnTH6q9UNr0i1OPaoIde35sZfYlY0RgRAJx+YijtsQYwNm6QzTi5AQ5JvuX8EPRsKD9zhTeyBBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T19:24:32.608899Z","bundle_sha256":"2f855aaf77143620d5841f05119e3b5c8a85682dadc39f8a7fbe432cada9dc81"}}