{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:BXLJTXXWUB3YJ4DIFYZKC25IQP","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":"e86e3f4d83abacda6ec6429614e784879e262175f31bafcba8ee8e1ae37b705c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T13:04:18Z","title_canon_sha256":"44ddd0da537a25ad528424397c1d93061d93bdb27f2b4c9975f17509b13009ca"},"schema_version":"1.0","source":{"id":"2605.31272","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.31272","created_at":"2026-06-01T01:04:08Z"},{"alias_kind":"arxiv_version","alias_value":"2605.31272v1","created_at":"2026-06-01T01:04:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.31272","created_at":"2026-06-01T01:04:08Z"},{"alias_kind":"pith_short_12","alias_value":"BXLJTXXWUB3Y","created_at":"2026-06-01T01:04:08Z"},{"alias_kind":"pith_short_16","alias_value":"BXLJTXXWUB3YJ4DI","created_at":"2026-06-01T01:04:08Z"},{"alias_kind":"pith_short_8","alias_value":"BXLJTXXW","created_at":"2026-06-01T01:04:08Z"}],"graph_snapshots":[{"event_id":"sha256:489f9845fa9cc7fd19e68b55068b04c57d28ccd932eea91083b549ff3e66b67d","target":"graph","created_at":"2026-06-01T01:04:08Z","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/2605.31272/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As predictive models are increasingly deployed in high-stakes settings such as credit approval, there is a growing need for post-hoc methods that provide recourse to affected individuals. Many such models operate on tabular data, where features correspond to real-world attributes. Recently, in-context learning (ICL) has enabled large language models to perform tabular prediction by conditioning on labeled examples at inference time, without explicit training. However, algorithmic recourse for tabular decision-making under ICL remains largely unexplored. In this work, we present the first study","authors_text":"Di Wang, Hongbin Lin, Jiaming Zhang, Lijie Hu, Shaopneg Fu, Wenshuo Dong","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T13:04:18Z","title":"Algorithmic Recourse of In-Context Learning for Tabular Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.31272","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":"sha256:6ec24e0e092bcf1c4399c5436fe1d82926f6d9be4f620ba96676f5697268fd00","target":"record","created_at":"2026-06-01T01:04:08Z","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":"e86e3f4d83abacda6ec6429614e784879e262175f31bafcba8ee8e1ae37b705c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-29T13:04:18Z","title_canon_sha256":"44ddd0da537a25ad528424397c1d93061d93bdb27f2b4c9975f17509b13009ca"},"schema_version":"1.0","source":{"id":"2605.31272","kind":"arxiv","version":1}},"canonical_sha256":"0dd699def6a07784f0682e32a16ba883c9f6e184f946bb4cf5353a8cd35c0f5f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0dd699def6a07784f0682e32a16ba883c9f6e184f946bb4cf5353a8cd35c0f5f","first_computed_at":"2026-06-01T01:04:08.136654Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-01T01:04:08.136654Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TMBY0/FF/zX32DCgbwT+A0OSPzaPQ3LFdYPykgN1hHIWLCDF4ou8RdJXTxuPetcDOYNU7w//+D6u4ojMRpa8AQ==","signature_status":"signed_v1","signed_at":"2026-06-01T01:04:08.137300Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.31272","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6ec24e0e092bcf1c4399c5436fe1d82926f6d9be4f620ba96676f5697268fd00","sha256:489f9845fa9cc7fd19e68b55068b04c57d28ccd932eea91083b549ff3e66b67d"],"state_sha256":"1a7ef2ddf6acea300ac13366fbe26bc2b747af0eef5d80813f834b9d6b2d7314"}