{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:BWULN2KFREFYPD3J6UBSXBDOON","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":"b96a2a1ebef3d498a2230cacb39b8acba79f5cd14e8f404ec4c7732fbf02ae69","cross_cats_sorted":["cs.AI","cs.CL","cs.PF"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-25T02:24:00Z","title_canon_sha256":"e382956c89c049c75055cd9255697dddad2d999ee7e26e0bf71beb43e95bd593"},"schema_version":"1.0","source":{"id":"2501.15030","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.15030","created_at":"2026-07-05T10:16:41Z"},{"alias_kind":"arxiv_version","alias_value":"2501.15030v2","created_at":"2026-07-05T10:16:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.15030","created_at":"2026-07-05T10:16:41Z"},{"alias_kind":"pith_short_12","alias_value":"BWULN2KFREFY","created_at":"2026-07-05T10:16:41Z"},{"alias_kind":"pith_short_16","alias_value":"BWULN2KFREFYPD3J","created_at":"2026-07-05T10:16:41Z"},{"alias_kind":"pith_short_8","alias_value":"BWULN2KF","created_at":"2026-07-05T10:16:41Z"}],"graph_snapshots":[{"event_id":"sha256:9eb9758d534ef48cd587a45703b4ff75917eff10372e136f68e73bc0ce573ac7","target":"graph","created_at":"2026-07-05T10:16:41Z","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/2501.15030/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Developers using LLMs and LLM-based agents in their applications have provided plenty of anecdotal evidence that in-context-learning (ICL) is fragile. In this paper, we show that in addition to the quantity and quality of examples, the order in which the in-context examples are listed in the prompt affects the output of the LLM and, consequently, their performance. While prior work has explored improving ICL through dataset-dependent techniques, we introduce OptiSeq, a purely inference-time, dataset-free optimization method that efficiently determines the best example order. OptiSeq leverages ","authors_text":"K. R. Jayaram, Nalini Venkatasubramanian, Praveen Venkateswaran, Rahul Atul Bhope, Vatche Isahagian, Vinod Muthusamy","cross_cats":["cs.AI","cs.CL","cs.PF"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-25T02:24:00Z","title":"OptiSeq: Ordering Examples On-The-Fly for In-Context Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.15030","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:b98365c9ead644d12450a97593ec469a78614b8856d2c5dbd808604f67f1df04","target":"record","created_at":"2026-07-05T10:16:41Z","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":"b96a2a1ebef3d498a2230cacb39b8acba79f5cd14e8f404ec4c7732fbf02ae69","cross_cats_sorted":["cs.AI","cs.CL","cs.PF"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-25T02:24:00Z","title_canon_sha256":"e382956c89c049c75055cd9255697dddad2d999ee7e26e0bf71beb43e95bd593"},"schema_version":"1.0","source":{"id":"2501.15030","kind":"arxiv","version":2}},"canonical_sha256":"0da8b6e945890b878f69f5032b846e7379a3376d7d9372d5b83e4422a2b6af93","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0da8b6e945890b878f69f5032b846e7379a3376d7d9372d5b83e4422a2b6af93","first_computed_at":"2026-07-05T10:16:41.170921Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:16:41.170921Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"y075MPHv1TkvgVDODqO4rd2mY+5CA4/aQa6yv2+ROMBZkKlUkgsX5IqmrYYXrG698JtpXk5NAUVrIHQ50igNDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:16:41.171367Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.15030","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b98365c9ead644d12450a97593ec469a78614b8856d2c5dbd808604f67f1df04","sha256:9eb9758d534ef48cd587a45703b4ff75917eff10372e136f68e73bc0ce573ac7"],"state_sha256":"fef1bc6db4969908e2f1bdc9b601c11be822ce2ee3f81b7d35a36c9c87fef186"}