{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:EKUAKL7FU6UQZMPTI7LC3XK7NI","short_pith_number":"pith:EKUAKL7F","canonical_record":{"source":{"id":"2205.09095","kind":"arxiv","version":7},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-18T17:41:37Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b2107200f63bb56bef19329b99ea801dd90d157401ae863fd7f0cc7c659a295e","abstract_canon_sha256":"68f6860359eb471149544dceca1465d9554af431191cc7354baed4434e125bdc"},"schema_version":"1.0"},"canonical_sha256":"22a8052fe5a7a90cb1f347d62ddd5f6a3a9bcd42852ea1355eba237be7976f31","source":{"kind":"arxiv","id":"2205.09095","version":7},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.09095","created_at":"2026-07-05T05:36:16Z"},{"alias_kind":"arxiv_version","alias_value":"2205.09095v7","created_at":"2026-07-05T05:36:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.09095","created_at":"2026-07-05T05:36:16Z"},{"alias_kind":"pith_short_12","alias_value":"EKUAKL7FU6UQ","created_at":"2026-07-05T05:36:16Z"},{"alias_kind":"pith_short_16","alias_value":"EKUAKL7FU6UQZMPT","created_at":"2026-07-05T05:36:16Z"},{"alias_kind":"pith_short_8","alias_value":"EKUAKL7F","created_at":"2026-07-05T05:36:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:EKUAKL7FU6UQZMPTI7LC3XK7NI","target":"record","payload":{"canonical_record":{"source":{"id":"2205.09095","kind":"arxiv","version":7},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-18T17:41:37Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b2107200f63bb56bef19329b99ea801dd90d157401ae863fd7f0cc7c659a295e","abstract_canon_sha256":"68f6860359eb471149544dceca1465d9554af431191cc7354baed4434e125bdc"},"schema_version":"1.0"},"canonical_sha256":"22a8052fe5a7a90cb1f347d62ddd5f6a3a9bcd42852ea1355eba237be7976f31","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:36:16.490491Z","signature_b64":"nOBIbX5dFtnc82o8WQ+uQMO7/CqpNDBBpMZmHjtQhiYZhPeQxHFwvkNwCZZwhl9zA0pbSU8Lv3/8exru+Ln6Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"22a8052fe5a7a90cb1f347d62ddd5f6a3a9bcd42852ea1355eba237be7976f31","last_reissued_at":"2026-07-05T05:36:16.490015Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:36:16.490015Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.09095","source_version":7,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:36:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wDgSC7xzfdrZXFQJBli7sbypZ2brj3+5Xq/Yocpoe+3YTiitJYAb/9wxiXv4C2ISp/cvRuajA0J5GSxDpcSeDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T13:55:36.501662Z"},"content_sha256":"4a1ff470404eac9bd4aeb2379004228a24ba7b7c5033cd5cc6922359cb25716c","schema_version":"1.0","event_id":"sha256:4a1ff470404eac9bd4aeb2379004228a24ba7b7c5033cd5cc6922359cb25716c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:EKUAKL7FU6UQZMPTI7LC3XK7NI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Achieving Risk Control in Online Learning Settings","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Liran Ringel, Shai Feldman, Stephen Bates, Yaniv Romano","submitted_at":"2022-05-18T17:41:37Z","abstract_excerpt":"To provide rigorous uncertainty quantification for online learning models, we develop a framework for constructing uncertainty sets that provably control risk -- such as coverage of confidence intervals, false negative rate, or F1 score -- in the online setting. This extends conformal prediction to apply to a larger class of online learning problems. Our method guarantees risk control at any user-specified level even when the underlying data distribution shifts drastically, even adversarially, over time in an unknown fashion. The technique we propose is highly flexible as it can be applied wit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.09095","kind":"arxiv","version":7},"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/2205.09095/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":"2026-07-05T05:36:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2HeauGTW9omsm2ySEJVp4JkLqPvP9cgWifr0GdkzmkJQmcCe13R4yEmaWPjO0n8p1VcPXNFcXVRcY6W5JZXZCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T13:55:36.502838Z"},"content_sha256":"624814453af02e1d5de05003c35f85e2a6c3faa4509ced6fe45e0dd62d5548a8","schema_version":"1.0","event_id":"sha256:624814453af02e1d5de05003c35f85e2a6c3faa4509ced6fe45e0dd62d5548a8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EKUAKL7FU6UQZMPTI7LC3XK7NI/bundle.json","state_url":"https://pith.science/pith/EKUAKL7FU6UQZMPTI7LC3XK7NI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EKUAKL7FU6UQZMPTI7LC3XK7NI/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":"2026-08-11T13:55:36Z","links":{"resolver":"https://pith.science/pith/EKUAKL7FU6UQZMPTI7LC3XK7NI","bundle":"https://pith.science/pith/EKUAKL7FU6UQZMPTI7LC3XK7NI/bundle.json","state":"https://pith.science/pith/EKUAKL7FU6UQZMPTI7LC3XK7NI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EKUAKL7FU6UQZMPTI7LC3XK7NI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:EKUAKL7FU6UQZMPTI7LC3XK7NI","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":"68f6860359eb471149544dceca1465d9554af431191cc7354baed4434e125bdc","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-18T17:41:37Z","title_canon_sha256":"b2107200f63bb56bef19329b99ea801dd90d157401ae863fd7f0cc7c659a295e"},"schema_version":"1.0","source":{"id":"2205.09095","kind":"arxiv","version":7}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.09095","created_at":"2026-07-05T05:36:16Z"},{"alias_kind":"arxiv_version","alias_value":"2205.09095v7","created_at":"2026-07-05T05:36:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.09095","created_at":"2026-07-05T05:36:16Z"},{"alias_kind":"pith_short_12","alias_value":"EKUAKL7FU6UQ","created_at":"2026-07-05T05:36:16Z"},{"alias_kind":"pith_short_16","alias_value":"EKUAKL7FU6UQZMPT","created_at":"2026-07-05T05:36:16Z"},{"alias_kind":"pith_short_8","alias_value":"EKUAKL7F","created_at":"2026-07-05T05:36:16Z"}],"graph_snapshots":[{"event_id":"sha256:624814453af02e1d5de05003c35f85e2a6c3faa4509ced6fe45e0dd62d5548a8","target":"graph","created_at":"2026-07-05T05:36:16Z","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/2205.09095/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"To provide rigorous uncertainty quantification for online learning models, we develop a framework for constructing uncertainty sets that provably control risk -- such as coverage of confidence intervals, false negative rate, or F1 score -- in the online setting. This extends conformal prediction to apply to a larger class of online learning problems. Our method guarantees risk control at any user-specified level even when the underlying data distribution shifts drastically, even adversarially, over time in an unknown fashion. The technique we propose is highly flexible as it can be applied wit","authors_text":"Liran Ringel, Shai Feldman, Stephen Bates, Yaniv Romano","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-18T17:41:37Z","title":"Achieving Risk Control in Online Learning Settings"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.09095","kind":"arxiv","version":7},"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":"sha256:4a1ff470404eac9bd4aeb2379004228a24ba7b7c5033cd5cc6922359cb25716c","target":"record","created_at":"2026-07-05T05:36:16Z","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":"68f6860359eb471149544dceca1465d9554af431191cc7354baed4434e125bdc","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-18T17:41:37Z","title_canon_sha256":"b2107200f63bb56bef19329b99ea801dd90d157401ae863fd7f0cc7c659a295e"},"schema_version":"1.0","source":{"id":"2205.09095","kind":"arxiv","version":7}},"canonical_sha256":"22a8052fe5a7a90cb1f347d62ddd5f6a3a9bcd42852ea1355eba237be7976f31","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"22a8052fe5a7a90cb1f347d62ddd5f6a3a9bcd42852ea1355eba237be7976f31","first_computed_at":"2026-07-05T05:36:16.490015Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:36:16.490015Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nOBIbX5dFtnc82o8WQ+uQMO7/CqpNDBBpMZmHjtQhiYZhPeQxHFwvkNwCZZwhl9zA0pbSU8Lv3/8exru+Ln6Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:36:16.490491Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.09095","source_kind":"arxiv","source_version":7}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4a1ff470404eac9bd4aeb2379004228a24ba7b7c5033cd5cc6922359cb25716c","sha256:624814453af02e1d5de05003c35f85e2a6c3faa4509ced6fe45e0dd62d5548a8"],"state_sha256":"2ac22a4122b609cf1a8c3373843da69c50885e8fdcee73500b88eb596f9a34d4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DxlswrGv/q6tM8EMvv5Qd9P5mQkhNc5gsVpscxmL1OqwAka2CdxkWucH6ncMtavoxM7R7LPmQFZQQV6IVc3nCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T13:55:36.513583Z","bundle_sha256":"24aa5a7324f9b2ce01ac28373c3a01669e5d20f4f810e5b519901a190013c7f4"}}