{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:FVTDAJCFWOK7FHKF4LMYUDHA5S","short_pith_number":"pith:FVTDAJCF","canonical_record":{"source":{"id":"2411.17941","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-26T23:28:54Z","cross_cats_sorted":[],"title_canon_sha256":"20fa29c3d3ddfd3b819d7b4f440b5328d75510a553fc0f6ec17aad70d7b0a1ae","abstract_canon_sha256":"b054cae56a2486a835dc78670e82e23ae4d9457ac19ffc6dbc9c58f3c619b393"},"schema_version":"1.0"},"canonical_sha256":"2d66302445b395f29d45e2d98a0ce0ec93c65958d74d9b827beecbb4aa0b36fa","source":{"kind":"arxiv","id":"2411.17941","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.17941","created_at":"2026-07-05T12:04:29Z"},{"alias_kind":"arxiv_version","alias_value":"2411.17941v3","created_at":"2026-07-05T12:04:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.17941","created_at":"2026-07-05T12:04:29Z"},{"alias_kind":"pith_short_12","alias_value":"FVTDAJCFWOK7","created_at":"2026-07-05T12:04:29Z"},{"alias_kind":"pith_short_16","alias_value":"FVTDAJCFWOK7FHKF","created_at":"2026-07-05T12:04:29Z"},{"alias_kind":"pith_short_8","alias_value":"FVTDAJCF","created_at":"2026-07-05T12:04:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:FVTDAJCFWOK7FHKF4LMYUDHA5S","target":"record","payload":{"canonical_record":{"source":{"id":"2411.17941","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-26T23:28:54Z","cross_cats_sorted":[],"title_canon_sha256":"20fa29c3d3ddfd3b819d7b4f440b5328d75510a553fc0f6ec17aad70d7b0a1ae","abstract_canon_sha256":"b054cae56a2486a835dc78670e82e23ae4d9457ac19ffc6dbc9c58f3c619b393"},"schema_version":"1.0"},"canonical_sha256":"2d66302445b395f29d45e2d98a0ce0ec93c65958d74d9b827beecbb4aa0b36fa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:04:29.434466Z","signature_b64":"cVMlGp86+NehiiKTnsxoRFVcVqmQwQJAHN8p3Hc8bUKJ5C4n/YX+9tZZlE18VGALYYYavG2TpgtUGm4jHHOIAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2d66302445b395f29d45e2d98a0ce0ec93c65958d74d9b827beecbb4aa0b36fa","last_reissued_at":"2026-07-05T12:04:29.433961Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:04:29.433961Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.17941","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":"2026-07-05T12:04:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kP9pZQXE43klKSsmmW5qwHAKyc+4bLZq3obk+y2Sr+KMWAbZfjid01PE30nsTdFwOkoVmy3kK16Nz67ztbtADA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T05:29:08.503654Z"},"content_sha256":"d8fbbdb6f97986ad085ec6025738657bc46b382679d456e58dde3a4d188dbaea","schema_version":"1.0","event_id":"sha256:d8fbbdb6f97986ad085ec6025738657bc46b382679d456e58dde3a4d188dbaea"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:FVTDAJCFWOK7FHKF4LMYUDHA5S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-Label Bayesian Active Learning with Inter-Label Relationships","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Joanne Enticott, Jueqing Lu, Lan Du, Xiaohao Yang, Yuanyuan Qi","submitted_at":"2024-11-26T23:28:54Z","abstract_excerpt":"The primary challenge of multi-label active learning, differing it from multi-class active learning, lies in assessing the informativeness of an indefinite number of labels while also accounting for the inherited label correlation. Existing studies either require substantial computational resources to leverage correlations or fail to fully explore label dependencies. Additionally, real-world scenarios often require addressing intrinsic biases stemming from imbalanced data distributions. In this paper, we propose a new multi-label active learning strategy to address both challenges. Our method "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.17941","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/2411.17941/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":"2026-07-05T12:04:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JSbd24JgIKaKvHz1UNYesO1vI3aSLRLZfs45z1OrXiowaWcFPlkNR0ZaHvu04Q57Fm8CDBcjBOkZj574Gti3Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T05:29:08.504172Z"},"content_sha256":"7cf875d2ef001d07e45aa4b5cbcca71b2d97dffc89692c3c8d87505d51ea967a","schema_version":"1.0","event_id":"sha256:7cf875d2ef001d07e45aa4b5cbcca71b2d97dffc89692c3c8d87505d51ea967a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FVTDAJCFWOK7FHKF4LMYUDHA5S/bundle.json","state_url":"https://pith.science/pith/FVTDAJCFWOK7FHKF4LMYUDHA5S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FVTDAJCFWOK7FHKF4LMYUDHA5S/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":"2026-08-13T05:29:08Z","links":{"resolver":"https://pith.science/pith/FVTDAJCFWOK7FHKF4LMYUDHA5S","bundle":"https://pith.science/pith/FVTDAJCFWOK7FHKF4LMYUDHA5S/bundle.json","state":"https://pith.science/pith/FVTDAJCFWOK7FHKF4LMYUDHA5S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FVTDAJCFWOK7FHKF4LMYUDHA5S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:FVTDAJCFWOK7FHKF4LMYUDHA5S","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":"b054cae56a2486a835dc78670e82e23ae4d9457ac19ffc6dbc9c58f3c619b393","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-26T23:28:54Z","title_canon_sha256":"20fa29c3d3ddfd3b819d7b4f440b5328d75510a553fc0f6ec17aad70d7b0a1ae"},"schema_version":"1.0","source":{"id":"2411.17941","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.17941","created_at":"2026-07-05T12:04:29Z"},{"alias_kind":"arxiv_version","alias_value":"2411.17941v3","created_at":"2026-07-05T12:04:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.17941","created_at":"2026-07-05T12:04:29Z"},{"alias_kind":"pith_short_12","alias_value":"FVTDAJCFWOK7","created_at":"2026-07-05T12:04:29Z"},{"alias_kind":"pith_short_16","alias_value":"FVTDAJCFWOK7FHKF","created_at":"2026-07-05T12:04:29Z"},{"alias_kind":"pith_short_8","alias_value":"FVTDAJCF","created_at":"2026-07-05T12:04:29Z"}],"graph_snapshots":[{"event_id":"sha256:7cf875d2ef001d07e45aa4b5cbcca71b2d97dffc89692c3c8d87505d51ea967a","target":"graph","created_at":"2026-07-05T12:04:29Z","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/2411.17941/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The primary challenge of multi-label active learning, differing it from multi-class active learning, lies in assessing the informativeness of an indefinite number of labels while also accounting for the inherited label correlation. Existing studies either require substantial computational resources to leverage correlations or fail to fully explore label dependencies. Additionally, real-world scenarios often require addressing intrinsic biases stemming from imbalanced data distributions. In this paper, we propose a new multi-label active learning strategy to address both challenges. Our method ","authors_text":"Joanne Enticott, Jueqing Lu, Lan Du, Xiaohao Yang, Yuanyuan Qi","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-26T23:28:54Z","title":"Multi-Label Bayesian Active Learning with Inter-Label Relationships"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.17941","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:d8fbbdb6f97986ad085ec6025738657bc46b382679d456e58dde3a4d188dbaea","target":"record","created_at":"2026-07-05T12:04:29Z","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":"b054cae56a2486a835dc78670e82e23ae4d9457ac19ffc6dbc9c58f3c619b393","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-26T23:28:54Z","title_canon_sha256":"20fa29c3d3ddfd3b819d7b4f440b5328d75510a553fc0f6ec17aad70d7b0a1ae"},"schema_version":"1.0","source":{"id":"2411.17941","kind":"arxiv","version":3}},"canonical_sha256":"2d66302445b395f29d45e2d98a0ce0ec93c65958d74d9b827beecbb4aa0b36fa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2d66302445b395f29d45e2d98a0ce0ec93c65958d74d9b827beecbb4aa0b36fa","first_computed_at":"2026-07-05T12:04:29.433961Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:04:29.433961Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cVMlGp86+NehiiKTnsxoRFVcVqmQwQJAHN8p3Hc8bUKJ5C4n/YX+9tZZlE18VGALYYYavG2TpgtUGm4jHHOIAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:04:29.434466Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.17941","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d8fbbdb6f97986ad085ec6025738657bc46b382679d456e58dde3a4d188dbaea","sha256:7cf875d2ef001d07e45aa4b5cbcca71b2d97dffc89692c3c8d87505d51ea967a"],"state_sha256":"43e103bcfc777b6d9fbbf45f9fa131ff3c16bb1441a22ceab73f753219459992"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/06PxQ3z+La6cD+9qLkS3dV4V5PWeRsT2wypkOTAdF5BRnTRC2+tfaz5EnJ/w9JyJonrh8rvIlbUoz/RKQmFAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T05:29:08.510432Z","bundle_sha256":"08d71d94c1ed3343c130e1887b4bac96c5dd96d1b96e3c3c4b7989495b245de8"}}