{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:4NHKGBDOPPBK6UNKSJFLT2EARY","short_pith_number":"pith:4NHKGBDO","canonical_record":{"source":{"id":"2104.06670","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-04-14T07:33:48Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"4ae55804161baa87a377d659229abcfe6dd5a62ddbe04bafd0943dbf280afb9e","abstract_canon_sha256":"17382dd15df0ab147b668a6de6ffbda8a5c9e8bb89bd7c96001b459065699285"},"schema_version":"1.0"},"canonical_sha256":"e34ea3046e7bc2af51aa924ab9e8808e12db0810871c1440af7ade3c0a1ddb50","source":{"kind":"arxiv","id":"2104.06670","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.06670","created_at":"2026-07-05T02:42:50Z"},{"alias_kind":"arxiv_version","alias_value":"2104.06670v2","created_at":"2026-07-05T02:42:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.06670","created_at":"2026-07-05T02:42:50Z"},{"alias_kind":"pith_short_12","alias_value":"4NHKGBDOPPBK","created_at":"2026-07-05T02:42:50Z"},{"alias_kind":"pith_short_16","alias_value":"4NHKGBDOPPBK6UNK","created_at":"2026-07-05T02:42:50Z"},{"alias_kind":"pith_short_8","alias_value":"4NHKGBDO","created_at":"2026-07-05T02:42:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:4NHKGBDOPPBK6UNKSJFLT2EARY","target":"record","payload":{"canonical_record":{"source":{"id":"2104.06670","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-04-14T07:33:48Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"4ae55804161baa87a377d659229abcfe6dd5a62ddbe04bafd0943dbf280afb9e","abstract_canon_sha256":"17382dd15df0ab147b668a6de6ffbda8a5c9e8bb89bd7c96001b459065699285"},"schema_version":"1.0"},"canonical_sha256":"e34ea3046e7bc2af51aa924ab9e8808e12db0810871c1440af7ade3c0a1ddb50","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:42:50.711410Z","signature_b64":"kL9qyIyAwT+dO4pZ5wXHmOv2rf3/GtWESC3dsIblolVGTvQ8WQaFoNiCTlXZn+w97CtLx/P1FMUgyiF69fHlCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e34ea3046e7bc2af51aa924ab9e8808e12db0810871c1440af7ade3c0a1ddb50","last_reissued_at":"2026-07-05T02:42:50.710953Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:42:50.710953Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.06670","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":"2026-07-05T02:42:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DvLLYeoLvUI7eXdutGdPYR2X5/80GvoX3xSTv6qeifaWwtLq2bo6ck9ZKF1CCkjyyCfcvYzWXyrxW9gStY/QCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T10:49:46.701265Z"},"content_sha256":"8f1331b925b0f16346d95089414c01ef1dd4851ca2204440ffdfb5be69b3498c","schema_version":"1.0","event_id":"sha256:8f1331b925b0f16346d95089414c01ef1dd4851ca2204440ffdfb5be69b3498c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:4NHKGBDOPPBK6UNKSJFLT2EARY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Explainable Multi-Party Learning: A Contrastive Knowledge Sharing Framework","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"A. K. Qin, Jiawei Li, Maoguo Gong, Yuan Gao, Yu Xie","submitted_at":"2021-04-14T07:33:48Z","abstract_excerpt":"Multi-party learning provides solutions for training joint models with decentralized data under legal and practical constraints. However, traditional multi-party learning approaches are confronted with obstacles such as system heterogeneity, statistical heterogeneity, and incentive design. How to deal with these challenges and further improve the efficiency and performance of multi-party learning has become an urgent problem to be solved. In this paper, we propose a novel contrastive multi-party learning framework for knowledge refinement and sharing with an accountable incentive mechanism. Si"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.06670","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/2104.06670/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":"2026-07-05T02:42:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1R7abGMWCBvkqaLy/m8bX2JsB4fl2/g/Du29Y9UuFP+E3ssxj+MYoyRyz2rAE2E6kteJQLCGU1ovGft0EQxJCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T10:49:46.701656Z"},"content_sha256":"da47cf97c09254256819e4131e635c0f03e8e3329622f2bb7a0d4e8e575d5282","schema_version":"1.0","event_id":"sha256:da47cf97c09254256819e4131e635c0f03e8e3329622f2bb7a0d4e8e575d5282"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4NHKGBDOPPBK6UNKSJFLT2EARY/bundle.json","state_url":"https://pith.science/pith/4NHKGBDOPPBK6UNKSJFLT2EARY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4NHKGBDOPPBK6UNKSJFLT2EARY/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":"2026-07-07T10:49:46Z","links":{"resolver":"https://pith.science/pith/4NHKGBDOPPBK6UNKSJFLT2EARY","bundle":"https://pith.science/pith/4NHKGBDOPPBK6UNKSJFLT2EARY/bundle.json","state":"https://pith.science/pith/4NHKGBDOPPBK6UNKSJFLT2EARY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4NHKGBDOPPBK6UNKSJFLT2EARY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:4NHKGBDOPPBK6UNKSJFLT2EARY","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":"17382dd15df0ab147b668a6de6ffbda8a5c9e8bb89bd7c96001b459065699285","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-04-14T07:33:48Z","title_canon_sha256":"4ae55804161baa87a377d659229abcfe6dd5a62ddbe04bafd0943dbf280afb9e"},"schema_version":"1.0","source":{"id":"2104.06670","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.06670","created_at":"2026-07-05T02:42:50Z"},{"alias_kind":"arxiv_version","alias_value":"2104.06670v2","created_at":"2026-07-05T02:42:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.06670","created_at":"2026-07-05T02:42:50Z"},{"alias_kind":"pith_short_12","alias_value":"4NHKGBDOPPBK","created_at":"2026-07-05T02:42:50Z"},{"alias_kind":"pith_short_16","alias_value":"4NHKGBDOPPBK6UNK","created_at":"2026-07-05T02:42:50Z"},{"alias_kind":"pith_short_8","alias_value":"4NHKGBDO","created_at":"2026-07-05T02:42:50Z"}],"graph_snapshots":[{"event_id":"sha256:da47cf97c09254256819e4131e635c0f03e8e3329622f2bb7a0d4e8e575d5282","target":"graph","created_at":"2026-07-05T02:42:50Z","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/2104.06670/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-party learning provides solutions for training joint models with decentralized data under legal and practical constraints. However, traditional multi-party learning approaches are confronted with obstacles such as system heterogeneity, statistical heterogeneity, and incentive design. How to deal with these challenges and further improve the efficiency and performance of multi-party learning has become an urgent problem to be solved. In this paper, we propose a novel contrastive multi-party learning framework for knowledge refinement and sharing with an accountable incentive mechanism. Si","authors_text":"A. K. Qin, Jiawei Li, Maoguo Gong, Yuan Gao, Yu Xie","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-04-14T07:33:48Z","title":"Towards Explainable Multi-Party Learning: A Contrastive Knowledge Sharing Framework"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.06670","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":"sha256:8f1331b925b0f16346d95089414c01ef1dd4851ca2204440ffdfb5be69b3498c","target":"record","created_at":"2026-07-05T02:42:50Z","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":"17382dd15df0ab147b668a6de6ffbda8a5c9e8bb89bd7c96001b459065699285","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-04-14T07:33:48Z","title_canon_sha256":"4ae55804161baa87a377d659229abcfe6dd5a62ddbe04bafd0943dbf280afb9e"},"schema_version":"1.0","source":{"id":"2104.06670","kind":"arxiv","version":2}},"canonical_sha256":"e34ea3046e7bc2af51aa924ab9e8808e12db0810871c1440af7ade3c0a1ddb50","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e34ea3046e7bc2af51aa924ab9e8808e12db0810871c1440af7ade3c0a1ddb50","first_computed_at":"2026-07-05T02:42:50.710953Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:42:50.710953Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kL9qyIyAwT+dO4pZ5wXHmOv2rf3/GtWESC3dsIblolVGTvQ8WQaFoNiCTlXZn+w97CtLx/P1FMUgyiF69fHlCA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:42:50.711410Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.06670","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8f1331b925b0f16346d95089414c01ef1dd4851ca2204440ffdfb5be69b3498c","sha256:da47cf97c09254256819e4131e635c0f03e8e3329622f2bb7a0d4e8e575d5282"],"state_sha256":"a2f41e2dde44c724b89ea3d9410106a104eef379f79407c08b32cae7d954cf41"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/PBbT6D4aEqSBivwBeb1jkeCrv2AYPpeXxGMPyFsfsJrM6WMj+8oZ93EPk+1AfgpsqB77s3OQf1vA8JCwUHHDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T10:49:46.703614Z","bundle_sha256":"297fffe1aa33c84a13d960c1ef99ad1b7501f0965b70a31c6dcb904c120c6f1d"}}