{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:YHWJ7PSNQI3MJ75VPEQC5JQBD2","short_pith_number":"pith:YHWJ7PSN","canonical_record":{"source":{"id":"2501.06429","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-11T04:03:29Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b85861628d9866f624d71ae70585fcf4cceede7bc835035702abd8063ba426c6","abstract_canon_sha256":"c4ca576b5bbb684522c88331e4953808fa8f64b55746abbb1fffeb3772ce8a0c"},"schema_version":"1.0"},"canonical_sha256":"c1ec9fbe4d8236c4ffb579202ea6011e9612ab1c206a1c8a4139bd1f4f0116bf","source":{"kind":"arxiv","id":"2501.06429","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.06429","created_at":"2026-07-05T10:00:03Z"},{"alias_kind":"arxiv_version","alias_value":"2501.06429v1","created_at":"2026-07-05T10:00:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.06429","created_at":"2026-07-05T10:00:03Z"},{"alias_kind":"pith_short_12","alias_value":"YHWJ7PSNQI3M","created_at":"2026-07-05T10:00:03Z"},{"alias_kind":"pith_short_16","alias_value":"YHWJ7PSNQI3MJ75V","created_at":"2026-07-05T10:00:03Z"},{"alias_kind":"pith_short_8","alias_value":"YHWJ7PSN","created_at":"2026-07-05T10:00:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:YHWJ7PSNQI3MJ75VPEQC5JQBD2","target":"record","payload":{"canonical_record":{"source":{"id":"2501.06429","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-11T04:03:29Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b85861628d9866f624d71ae70585fcf4cceede7bc835035702abd8063ba426c6","abstract_canon_sha256":"c4ca576b5bbb684522c88331e4953808fa8f64b55746abbb1fffeb3772ce8a0c"},"schema_version":"1.0"},"canonical_sha256":"c1ec9fbe4d8236c4ffb579202ea6011e9612ab1c206a1c8a4139bd1f4f0116bf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:00:03.143901Z","signature_b64":"/ep94dB0axYrRexiJ83ez16YmfVaPETSdS8pbAGx/ift65tDU+cqEFnfhVvCI6nCy20mmCr/SSCPoDhjlFfXDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c1ec9fbe4d8236c4ffb579202ea6011e9612ab1c206a1c8a4139bd1f4f0116bf","last_reissued_at":"2026-07-05T10:00:03.143524Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:00:03.143524Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.06429","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":"2026-07-05T10:00:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jMzy4jxLRVt0ngHJ4rJuIaLdg9xbqiRn3vQ5Ts5BPpYSzPlEmddwjPKFgBXJRpIpDqUvbWtYwd3PAT2IBfwcCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T21:32:38.214527Z"},"content_sha256":"8212312377c80b9cbf63488f132da4f2eb0c209031b7aec21fcc82bf6e0168ec","schema_version":"1.0","event_id":"sha256:8212312377c80b9cbf63488f132da4f2eb0c209031b7aec21fcc82bf6e0168ec"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:YHWJ7PSNQI3MJ75VPEQC5JQBD2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Reliable Imputed-Sample Assisted Vertical Federated Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Baoyuan Wu, Hongjian Dou, Lei Liu, Li Liu, Shaoguo Liu, Yaopei Zeng","submitted_at":"2025-01-11T04:03:29Z","abstract_excerpt":"Vertical Federated Learning (VFL) is a well-known FL variant that enables multiple parties to collaboratively train a model without sharing their raw data. Existing VFL approaches focus on overlapping samples among different parties, while their performance is constrained by the limited number of these samples, leaving numerous non-overlapping samples unexplored. Some previous work has explored techniques for imputing missing values in samples, but often without adequate attention to the quality of the imputed samples. To address this issue, we propose a Reliable Imputed-Sample Assisted (RISA)"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.06429","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/2501.06429/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":"2026-07-05T10:00:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7yODtohlMlnKs70EHIZQDnRSoZH+S0lW2ENsecMvdgbhFJpZC22Ap1Us/5eDIFAaI3D5X2xckdYY6l2lXNWkBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T21:32:38.215195Z"},"content_sha256":"15420c151c90aab5cf6ab396ff0a5bcd3bdad93aa28e8c22b415ca255766724f","schema_version":"1.0","event_id":"sha256:15420c151c90aab5cf6ab396ff0a5bcd3bdad93aa28e8c22b415ca255766724f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YHWJ7PSNQI3MJ75VPEQC5JQBD2/bundle.json","state_url":"https://pith.science/pith/YHWJ7PSNQI3MJ75VPEQC5JQBD2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YHWJ7PSNQI3MJ75VPEQC5JQBD2/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":"2026-08-16T21:32:38Z","links":{"resolver":"https://pith.science/pith/YHWJ7PSNQI3MJ75VPEQC5JQBD2","bundle":"https://pith.science/pith/YHWJ7PSNQI3MJ75VPEQC5JQBD2/bundle.json","state":"https://pith.science/pith/YHWJ7PSNQI3MJ75VPEQC5JQBD2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YHWJ7PSNQI3MJ75VPEQC5JQBD2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:YHWJ7PSNQI3MJ75VPEQC5JQBD2","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":"c4ca576b5bbb684522c88331e4953808fa8f64b55746abbb1fffeb3772ce8a0c","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-11T04:03:29Z","title_canon_sha256":"b85861628d9866f624d71ae70585fcf4cceede7bc835035702abd8063ba426c6"},"schema_version":"1.0","source":{"id":"2501.06429","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.06429","created_at":"2026-07-05T10:00:03Z"},{"alias_kind":"arxiv_version","alias_value":"2501.06429v1","created_at":"2026-07-05T10:00:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.06429","created_at":"2026-07-05T10:00:03Z"},{"alias_kind":"pith_short_12","alias_value":"YHWJ7PSNQI3M","created_at":"2026-07-05T10:00:03Z"},{"alias_kind":"pith_short_16","alias_value":"YHWJ7PSNQI3MJ75V","created_at":"2026-07-05T10:00:03Z"},{"alias_kind":"pith_short_8","alias_value":"YHWJ7PSN","created_at":"2026-07-05T10:00:03Z"}],"graph_snapshots":[{"event_id":"sha256:15420c151c90aab5cf6ab396ff0a5bcd3bdad93aa28e8c22b415ca255766724f","target":"graph","created_at":"2026-07-05T10:00:03Z","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/2501.06429/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vertical Federated Learning (VFL) is a well-known FL variant that enables multiple parties to collaboratively train a model without sharing their raw data. Existing VFL approaches focus on overlapping samples among different parties, while their performance is constrained by the limited number of these samples, leaving numerous non-overlapping samples unexplored. Some previous work has explored techniques for imputing missing values in samples, but often without adequate attention to the quality of the imputed samples. To address this issue, we propose a Reliable Imputed-Sample Assisted (RISA)","authors_text":"Baoyuan Wu, Hongjian Dou, Lei Liu, Li Liu, Shaoguo Liu, Yaopei Zeng","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-11T04:03:29Z","title":"Reliable Imputed-Sample Assisted Vertical Federated Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.06429","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":"sha256:8212312377c80b9cbf63488f132da4f2eb0c209031b7aec21fcc82bf6e0168ec","target":"record","created_at":"2026-07-05T10:00:03Z","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":"c4ca576b5bbb684522c88331e4953808fa8f64b55746abbb1fffeb3772ce8a0c","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-11T04:03:29Z","title_canon_sha256":"b85861628d9866f624d71ae70585fcf4cceede7bc835035702abd8063ba426c6"},"schema_version":"1.0","source":{"id":"2501.06429","kind":"arxiv","version":1}},"canonical_sha256":"c1ec9fbe4d8236c4ffb579202ea6011e9612ab1c206a1c8a4139bd1f4f0116bf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c1ec9fbe4d8236c4ffb579202ea6011e9612ab1c206a1c8a4139bd1f4f0116bf","first_computed_at":"2026-07-05T10:00:03.143524Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:00:03.143524Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/ep94dB0axYrRexiJ83ez16YmfVaPETSdS8pbAGx/ift65tDU+cqEFnfhVvCI6nCy20mmCr/SSCPoDhjlFfXDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:00:03.143901Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.06429","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8212312377c80b9cbf63488f132da4f2eb0c209031b7aec21fcc82bf6e0168ec","sha256:15420c151c90aab5cf6ab396ff0a5bcd3bdad93aa28e8c22b415ca255766724f"],"state_sha256":"41d024a72953a187fa2099ff06d5896e9baf06b034bc34a9dbf528a38c6dc6da"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uhrhjazXJMOAYybtjfA87u/N0Xy7nX8sjpHZsw3jfzexvNlOxVoC4SeZM26F8+T+IPFM/oNQVF3F2O2yzl4RCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T21:32:38.220910Z","bundle_sha256":"031ab66771b60a10703704aefb3e8512256b3ce12538dca0a5f4f46202babdb6"}}