{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:UVXQ5KJCKJ2OUCHOESUPSY2XOJ","short_pith_number":"pith:UVXQ5KJC","canonical_record":{"source":{"id":"2605.25590","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2026-05-25T08:40:32Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"07cfdc17d99cf4cd8fd35b1fba6a9ed97c0f58b0c2ac71ffa40ade563d03ca4a","abstract_canon_sha256":"28d2dfb4f17690b50dfb70b456faf987e92e42b72107d832d85cc07d93965588"},"schema_version":"1.0"},"canonical_sha256":"a56f0ea9225274ea08ee24a8f963577275e37f8df821d3b4bca86a35fba1f0ca","source":{"kind":"arxiv","id":"2605.25590","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.25590","created_at":"2026-05-26T02:04:44Z"},{"alias_kind":"arxiv_version","alias_value":"2605.25590v1","created_at":"2026-05-26T02:04:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.25590","created_at":"2026-05-26T02:04:44Z"},{"alias_kind":"pith_short_12","alias_value":"UVXQ5KJCKJ2O","created_at":"2026-05-26T02:04:44Z"},{"alias_kind":"pith_short_16","alias_value":"UVXQ5KJCKJ2OUCHO","created_at":"2026-05-26T02:04:44Z"},{"alias_kind":"pith_short_8","alias_value":"UVXQ5KJC","created_at":"2026-05-26T02:04:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:UVXQ5KJCKJ2OUCHOESUPSY2XOJ","target":"record","payload":{"canonical_record":{"source":{"id":"2605.25590","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2026-05-25T08:40:32Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"07cfdc17d99cf4cd8fd35b1fba6a9ed97c0f58b0c2ac71ffa40ade563d03ca4a","abstract_canon_sha256":"28d2dfb4f17690b50dfb70b456faf987e92e42b72107d832d85cc07d93965588"},"schema_version":"1.0"},"canonical_sha256":"a56f0ea9225274ea08ee24a8f963577275e37f8df821d3b4bca86a35fba1f0ca","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T02:04:44.541020Z","signature_b64":"NzsgNK0N6ifx3r1TgCw1tCz0dyN7Z4hE6xYjqNY2UJ3wZgDWXcbEupgQgqEthSAv6VhWRc1c+gKJ18cUvoLnDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a56f0ea9225274ea08ee24a8f963577275e37f8df821d3b4bca86a35fba1f0ca","last_reissued_at":"2026-05-26T02:04:44.540418Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T02:04:44.540418Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.25590","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":"2026-05-26T02:04:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BPTu0+56tWKV3CKAcYBfgBGxVoXewZRdRqPmm65f2L5laozz27OdSoyN2aPModgE6dekv4mjqfXVt96Q0lmfDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T20:17:54.095609Z"},"content_sha256":"728435b68c0a1761171546225b1283775d8b1756e218397941448b3b6da05bc9","schema_version":"1.0","event_id":"sha256:728435b68c0a1761171546225b1283775d8b1756e218397941448b3b6da05bc9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:UVXQ5KJCKJ2OUCHOESUPSY2XOJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Nonstationary Generalized Linear Bandits with Discounted Online Mirror Descent","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Joongkyu Lee, Min-hwan Oh","submitted_at":"2026-05-25T08:40:32Z","abstract_excerpt":"We study nonstationary generalized linear bandits (GLBs), where the expected reward is modeled through a nonlinear link function with an unknown time-varying parameter. This framework encompasses a broad class of reward models, including linear, Bernoulli, and binomial rewards. Existing approaches are predominantly based on maximum-likelihood estimation (MLE), using sliding-window, restart, or discounting mechanisms to handle nonstationarity. Although these methods achieve statistically efficient regret guarantees, they generally require revisiting past observations at every round, which leads"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.25590","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/2605.25590/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":"2026-05-26T02:04:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"75uy7rveyq2mfKcuA6tsYCRY3ku+mTj5ER4slwnZlM8A08JvAu77mQJt7HZ6gZtL5B1HXQCQ2xKj3oKciRyvDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T20:17:54.096013Z"},"content_sha256":"fe6118b1e36380b0b785c33ef46654dabc6bc3478e841f7ec2ac3f7e24b37afb","schema_version":"1.0","event_id":"sha256:fe6118b1e36380b0b785c33ef46654dabc6bc3478e841f7ec2ac3f7e24b37afb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UVXQ5KJCKJ2OUCHOESUPSY2XOJ/bundle.json","state_url":"https://pith.science/pith/UVXQ5KJCKJ2OUCHOESUPSY2XOJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UVXQ5KJCKJ2OUCHOESUPSY2XOJ/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":"2026-06-01T20:17:54Z","links":{"resolver":"https://pith.science/pith/UVXQ5KJCKJ2OUCHOESUPSY2XOJ","bundle":"https://pith.science/pith/UVXQ5KJCKJ2OUCHOESUPSY2XOJ/bundle.json","state":"https://pith.science/pith/UVXQ5KJCKJ2OUCHOESUPSY2XOJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UVXQ5KJCKJ2OUCHOESUPSY2XOJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:UVXQ5KJCKJ2OUCHOESUPSY2XOJ","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":"28d2dfb4f17690b50dfb70b456faf987e92e42b72107d832d85cc07d93965588","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2026-05-25T08:40:32Z","title_canon_sha256":"07cfdc17d99cf4cd8fd35b1fba6a9ed97c0f58b0c2ac71ffa40ade563d03ca4a"},"schema_version":"1.0","source":{"id":"2605.25590","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.25590","created_at":"2026-05-26T02:04:44Z"},{"alias_kind":"arxiv_version","alias_value":"2605.25590v1","created_at":"2026-05-26T02:04:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.25590","created_at":"2026-05-26T02:04:44Z"},{"alias_kind":"pith_short_12","alias_value":"UVXQ5KJCKJ2O","created_at":"2026-05-26T02:04:44Z"},{"alias_kind":"pith_short_16","alias_value":"UVXQ5KJCKJ2OUCHO","created_at":"2026-05-26T02:04:44Z"},{"alias_kind":"pith_short_8","alias_value":"UVXQ5KJC","created_at":"2026-05-26T02:04:44Z"}],"graph_snapshots":[{"event_id":"sha256:fe6118b1e36380b0b785c33ef46654dabc6bc3478e841f7ec2ac3f7e24b37afb","target":"graph","created_at":"2026-05-26T02:04:44Z","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/2605.25590/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We study nonstationary generalized linear bandits (GLBs), where the expected reward is modeled through a nonlinear link function with an unknown time-varying parameter. This framework encompasses a broad class of reward models, including linear, Bernoulli, and binomial rewards. Existing approaches are predominantly based on maximum-likelihood estimation (MLE), using sliding-window, restart, or discounting mechanisms to handle nonstationarity. Although these methods achieve statistically efficient regret guarantees, they generally require revisiting past observations at every round, which leads","authors_text":"Joongkyu Lee, Min-hwan Oh","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2026-05-25T08:40:32Z","title":"Nonstationary Generalized Linear Bandits with Discounted Online Mirror Descent"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.25590","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":"sha256:728435b68c0a1761171546225b1283775d8b1756e218397941448b3b6da05bc9","target":"record","created_at":"2026-05-26T02:04:44Z","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":"28d2dfb4f17690b50dfb70b456faf987e92e42b72107d832d85cc07d93965588","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2026-05-25T08:40:32Z","title_canon_sha256":"07cfdc17d99cf4cd8fd35b1fba6a9ed97c0f58b0c2ac71ffa40ade563d03ca4a"},"schema_version":"1.0","source":{"id":"2605.25590","kind":"arxiv","version":1}},"canonical_sha256":"a56f0ea9225274ea08ee24a8f963577275e37f8df821d3b4bca86a35fba1f0ca","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a56f0ea9225274ea08ee24a8f963577275e37f8df821d3b4bca86a35fba1f0ca","first_computed_at":"2026-05-26T02:04:44.540418Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T02:04:44.540418Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NzsgNK0N6ifx3r1TgCw1tCz0dyN7Z4hE6xYjqNY2UJ3wZgDWXcbEupgQgqEthSAv6VhWRc1c+gKJ18cUvoLnDA==","signature_status":"signed_v1","signed_at":"2026-05-26T02:04:44.541020Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.25590","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:728435b68c0a1761171546225b1283775d8b1756e218397941448b3b6da05bc9","sha256:fe6118b1e36380b0b785c33ef46654dabc6bc3478e841f7ec2ac3f7e24b37afb"],"state_sha256":"d899ff41634f30c3c55b7e3d2d133c14ea8b7c57e8198d76e7c0f303fe49e04b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fiWTS+DTLdctko0v8ZUzFBnfjVcEpkexjeBhGDAiLeJJxQxO5VLrZBGcxaXIi6JNJOaJG1dsbDhpwSm8hGN4DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T20:17:54.098061Z","bundle_sha256":"1497e891c5e8466b65cb78d8606aab3301b9af00667c23205bfacbfcd19c3008"}}