{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:FJQKKLJEYWQUZFSJKMPISDPMKY","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":"73953c85279e8c0f04ee08b77c1aaeb2adb6783fa2dbc64d5b379b247b28e5cc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-12T06:42:10Z","title_canon_sha256":"63829a33ea9aed9f09b3d55204d8dffceffaa4a52d01e5725b68e3b0567276de"},"schema_version":"1.0","source":{"id":"2508.08673","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.08673","created_at":"2026-07-05T12:02:05Z"},{"alias_kind":"arxiv_version","alias_value":"2508.08673v2","created_at":"2026-07-05T12:02:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.08673","created_at":"2026-07-05T12:02:05Z"},{"alias_kind":"pith_short_12","alias_value":"FJQKKLJEYWQU","created_at":"2026-07-05T12:02:05Z"},{"alias_kind":"pith_short_16","alias_value":"FJQKKLJEYWQUZFSJ","created_at":"2026-07-05T12:02:05Z"},{"alias_kind":"pith_short_8","alias_value":"FJQKKLJE","created_at":"2026-07-05T12:02:05Z"}],"graph_snapshots":[{"event_id":"sha256:7c0b229595c90fd8a0d921796b8627bb26b160fbfa440038555f4811887bf174","target":"graph","created_at":"2026-07-05T12:02:05Z","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/2508.08673/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper investigates the expected excess risk of in-context learning (ICL) for multiclass classification. We formalize each task as a sequence of labeled examples followed by a query input; a pretrained model then estimates the query's conditional class probabilities. The expected excess risk is defined as the average truncated Kullback-Leibler (KL) divergence between the predicted and true conditional class distributions over a specified family of tasks. We establish a new oracle inequality for this risk, based on KL divergence, in multiclass classification. This yields tight upper and low","authors_text":"Chenrui Liu, Chuanlong Xie, Falong Tan, Lixing Zhu, Yicheng Zeng","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-12T06:42:10Z","title":"In-Context Learning as Nonparametric Conditional Probability Estimation: Risk Bounds and Optimality"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.08673","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":"sha256:54986073ae3bc5f06f4430258b6d7ce3aa8d125157a1744140863405940ebce8","target":"record","created_at":"2026-07-05T12:02:05Z","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":"73953c85279e8c0f04ee08b77c1aaeb2adb6783fa2dbc64d5b379b247b28e5cc","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2025-08-12T06:42:10Z","title_canon_sha256":"63829a33ea9aed9f09b3d55204d8dffceffaa4a52d01e5725b68e3b0567276de"},"schema_version":"1.0","source":{"id":"2508.08673","kind":"arxiv","version":2}},"canonical_sha256":"2a60a52d24c5a14c9649531e890dec5628c671c935c197886895f7afd8306aff","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2a60a52d24c5a14c9649531e890dec5628c671c935c197886895f7afd8306aff","first_computed_at":"2026-07-05T12:02:05.650798Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:02:05.650798Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1QgrjZuijJa+ZSGeYV6ACzf+R1JNrHn/0HMXLbTufjnxfkYxXkNLCfgZzywNrp5LtpAfGptoY3sH1YFBfAB6CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:02:05.652021Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.08673","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:54986073ae3bc5f06f4430258b6d7ce3aa8d125157a1744140863405940ebce8","sha256:7c0b229595c90fd8a0d921796b8627bb26b160fbfa440038555f4811887bf174"],"state_sha256":"9e0a95bc4fa12afc99963ce4d3540ca32d2fbec823303e047597b0b01a31c60b"}