{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:2GGME7DSS2XVLDTWLSRUKIVOHG","short_pith_number":"pith:2GGME7DS","canonical_record":{"source":{"id":"2312.11034","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-18T09:09:52Z","cross_cats_sorted":[],"title_canon_sha256":"abc3b94fea44dbf13cdce86824d462cad384d9ea42399e86c038bcd5cf992c0c","abstract_canon_sha256":"6c161d0f6352d8f905887bce1ed8b193f944a123fe75041977cea0a4cec9a870"},"schema_version":"1.0"},"canonical_sha256":"d18cc27c7296af558e765ca34522ae39a9f0bc0522e69122521806558170836a","source":{"kind":"arxiv","id":"2312.11034","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.11034","created_at":"2026-07-05T08:01:35Z"},{"alias_kind":"arxiv_version","alias_value":"2312.11034v3","created_at":"2026-07-05T08:01:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.11034","created_at":"2026-07-05T08:01:35Z"},{"alias_kind":"pith_short_12","alias_value":"2GGME7DSS2XV","created_at":"2026-07-05T08:01:35Z"},{"alias_kind":"pith_short_16","alias_value":"2GGME7DSS2XVLDTW","created_at":"2026-07-05T08:01:35Z"},{"alias_kind":"pith_short_8","alias_value":"2GGME7DS","created_at":"2026-07-05T08:01:35Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:2GGME7DSS2XVLDTWLSRUKIVOHG","target":"record","payload":{"canonical_record":{"source":{"id":"2312.11034","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-18T09:09:52Z","cross_cats_sorted":[],"title_canon_sha256":"abc3b94fea44dbf13cdce86824d462cad384d9ea42399e86c038bcd5cf992c0c","abstract_canon_sha256":"6c161d0f6352d8f905887bce1ed8b193f944a123fe75041977cea0a4cec9a870"},"schema_version":"1.0"},"canonical_sha256":"d18cc27c7296af558e765ca34522ae39a9f0bc0522e69122521806558170836a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:01:35.895949Z","signature_b64":"BAIho9bDaSeBpN7XfpkjsG3G3UsJ4YWQ0UkP9r816gwaJagVTkfn9hwDRPxZzN/Ygs+zR1q08CTj26NA9S1nDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d18cc27c7296af558e765ca34522ae39a9f0bc0522e69122521806558170836a","last_reissued_at":"2026-07-05T08:01:35.895389Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:01:35.895389Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.11034","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":"2026-07-05T08:01:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/p5ulrKf30LnVBHv+6q68wlVYq0ckRqur+SDtAmH1Yem2Cd7cPy9XW824YtDfoNOslu8hvAgn1/hkc4QnEdvAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T23:51:49.305125Z"},"content_sha256":"6bd81d23b08f44e0535389a9960e2b1efc4c5d2f5bd9203704feea7cdade91c1","schema_version":"1.0","event_id":"sha256:6bd81d23b08f44e0535389a9960e2b1efc4c5d2f5bd9203704feea7cdade91c1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:2GGME7DSS2XVLDTWLSRUKIVOHG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Appeal: Allow Mislabeled Samples the Chance to be Rectified in Partial Label Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Chongjie Si, Wei Shen, Xiaokang Yang, Xuehui Wang, Yan Wang","submitted_at":"2023-12-18T09:09:52Z","abstract_excerpt":"In partial label learning (PLL), each instance is associated with a set of candidate labels among which only one is ground-truth. The majority of the existing works focuses on constructing robust classifiers to estimate the labeling confidence of candidate labels in order to identify the correct one. However, these methods usually struggle to identify and rectify mislabeled samples. To help these mislabeled samples \"appeal\" for themselves and help existing PLL methods identify and rectify mislabeled samples, in this paper, we propose the first appeal-based PLL framework. Specifically, we intro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.11034","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/2312.11034/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":"2026-07-05T08:01:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"No99eqkhGgfrVBC0agiH5XDHrLENRVJQh9QJTZR9d29zY5GmBaineQHjYQrl+7Ta07w+Xo28j24qRv8WAMXyAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T23:51:49.305761Z"},"content_sha256":"7155355a3cd276f53153f495747e022017aa605bf7065ce2a90aadd329875277","schema_version":"1.0","event_id":"sha256:7155355a3cd276f53153f495747e022017aa605bf7065ce2a90aadd329875277"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2GGME7DSS2XVLDTWLSRUKIVOHG/bundle.json","state_url":"https://pith.science/pith/2GGME7DSS2XVLDTWLSRUKIVOHG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2GGME7DSS2XVLDTWLSRUKIVOHG/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":"2026-08-08T23:51:49Z","links":{"resolver":"https://pith.science/pith/2GGME7DSS2XVLDTWLSRUKIVOHG","bundle":"https://pith.science/pith/2GGME7DSS2XVLDTWLSRUKIVOHG/bundle.json","state":"https://pith.science/pith/2GGME7DSS2XVLDTWLSRUKIVOHG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2GGME7DSS2XVLDTWLSRUKIVOHG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:2GGME7DSS2XVLDTWLSRUKIVOHG","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":"6c161d0f6352d8f905887bce1ed8b193f944a123fe75041977cea0a4cec9a870","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-18T09:09:52Z","title_canon_sha256":"abc3b94fea44dbf13cdce86824d462cad384d9ea42399e86c038bcd5cf992c0c"},"schema_version":"1.0","source":{"id":"2312.11034","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.11034","created_at":"2026-07-05T08:01:35Z"},{"alias_kind":"arxiv_version","alias_value":"2312.11034v3","created_at":"2026-07-05T08:01:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.11034","created_at":"2026-07-05T08:01:35Z"},{"alias_kind":"pith_short_12","alias_value":"2GGME7DSS2XV","created_at":"2026-07-05T08:01:35Z"},{"alias_kind":"pith_short_16","alias_value":"2GGME7DSS2XVLDTW","created_at":"2026-07-05T08:01:35Z"},{"alias_kind":"pith_short_8","alias_value":"2GGME7DS","created_at":"2026-07-05T08:01:35Z"}],"graph_snapshots":[{"event_id":"sha256:7155355a3cd276f53153f495747e022017aa605bf7065ce2a90aadd329875277","target":"graph","created_at":"2026-07-05T08:01:35Z","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/2312.11034/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In partial label learning (PLL), each instance is associated with a set of candidate labels among which only one is ground-truth. The majority of the existing works focuses on constructing robust classifiers to estimate the labeling confidence of candidate labels in order to identify the correct one. However, these methods usually struggle to identify and rectify mislabeled samples. To help these mislabeled samples \"appeal\" for themselves and help existing PLL methods identify and rectify mislabeled samples, in this paper, we propose the first appeal-based PLL framework. Specifically, we intro","authors_text":"Chongjie Si, Wei Shen, Xiaokang Yang, Xuehui Wang, Yan Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-18T09:09:52Z","title":"Appeal: Allow Mislabeled Samples the Chance to be Rectified in Partial Label Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.11034","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":"sha256:6bd81d23b08f44e0535389a9960e2b1efc4c5d2f5bd9203704feea7cdade91c1","target":"record","created_at":"2026-07-05T08:01:35Z","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":"6c161d0f6352d8f905887bce1ed8b193f944a123fe75041977cea0a4cec9a870","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-12-18T09:09:52Z","title_canon_sha256":"abc3b94fea44dbf13cdce86824d462cad384d9ea42399e86c038bcd5cf992c0c"},"schema_version":"1.0","source":{"id":"2312.11034","kind":"arxiv","version":3}},"canonical_sha256":"d18cc27c7296af558e765ca34522ae39a9f0bc0522e69122521806558170836a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d18cc27c7296af558e765ca34522ae39a9f0bc0522e69122521806558170836a","first_computed_at":"2026-07-05T08:01:35.895389Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:01:35.895389Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BAIho9bDaSeBpN7XfpkjsG3G3UsJ4YWQ0UkP9r816gwaJagVTkfn9hwDRPxZzN/Ygs+zR1q08CTj26NA9S1nDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:01:35.895949Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.11034","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6bd81d23b08f44e0535389a9960e2b1efc4c5d2f5bd9203704feea7cdade91c1","sha256:7155355a3cd276f53153f495747e022017aa605bf7065ce2a90aadd329875277"],"state_sha256":"8fcc98eb450e50fe20d2d0c74affbfc40dd837b474ac98a60b17f50a44778186"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5IQpLcbNDJ/BzbWdJaZFhOizKaIkZMIdRcs9T9VcjV7zGaRea38yHBfOQYtrwTvXYVIip7RS7YBy7PU5dYO6BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T23:51:49.309950Z","bundle_sha256":"731670dbf45f077deae0e15da68388a8ba9f891673d72c28f1999fb14395926c"}}