{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:I5MAQ3YUOT5TQJORUYKHXKFOXK","short_pith_number":"pith:I5MAQ3YU","schema_version":"1.0","canonical_sha256":"4758086f1474fb3825d1a6147ba8aebaa1b9805eff1add9351d47ebc77d1e43e","source":{"kind":"arxiv","id":"2502.08662","version":3},"attestation_state":"computed","paper":{"title":"RoToR: Towards More Reliable Responses for Order-Invariant Inputs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Dongha Ahn, HyungJoo Jang, Minkyu Jung, Seung-won Hwang, Soyoung Yoon, Youngwon Lee","submitted_at":"2025-02-10T09:34:15Z","abstract_excerpt":"Mitigating positional bias of language models (LMs) for listwise inputs is a well-known and important problem (e.g., lost-in-the-middle). While zero-shot order-invariant LMs have been proposed to solve this issue, their success on practical listwise problems has been limited. In this work, as a first contribution, we identify and overcome two limitations to make zero-shot invariant LMs more practical: (1) training and inference distribution mismatch arising from modifying positional ID assignments to enforce invariance, and (2) failure to adapt to mixture of order-invariant and sensitive input"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2502.08662","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-10T09:34:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1618b7357733a22007c740fdca89972cc7ca0ea688b3682b01e11e1e57fb5de0","abstract_canon_sha256":"11572d302b08aabfb763b45d17334f90650105478da254461e6e06c7c2985d8e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:14:03.831847Z","signature_b64":"v4obyYaalBjEZmm3IUWXYTRRrPDvj7hhEAHkqFzUzh+6OCypf5CUrbvfuIOUZtJxDHFY8xAboy3YzOfIuRjECA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4758086f1474fb3825d1a6147ba8aebaa1b9805eff1add9351d47ebc77d1e43e","last_reissued_at":"2026-07-05T11:14:03.831290Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:14:03.831290Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"RoToR: Towards More Reliable Responses for Order-Invariant Inputs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Dongha Ahn, HyungJoo Jang, Minkyu Jung, Seung-won Hwang, Soyoung Yoon, Youngwon Lee","submitted_at":"2025-02-10T09:34:15Z","abstract_excerpt":"Mitigating positional bias of language models (LMs) for listwise inputs is a well-known and important problem (e.g., lost-in-the-middle). While zero-shot order-invariant LMs have been proposed to solve this issue, their success on practical listwise problems has been limited. In this work, as a first contribution, we identify and overcome two limitations to make zero-shot invariant LMs more practical: (1) training and inference distribution mismatch arising from modifying positional ID assignments to enforce invariance, and (2) failure to adapt to mixture of order-invariant and sensitive input"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.08662","kind":"arxiv","version":3},"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/2502.08662/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2502.08662","created_at":"2026-07-05T11:14:03.831369+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.08662v3","created_at":"2026-07-05T11:14:03.831369+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.08662","created_at":"2026-07-05T11:14:03.831369+00:00"},{"alias_kind":"pith_short_12","alias_value":"I5MAQ3YUOT5T","created_at":"2026-07-05T11:14:03.831369+00:00"},{"alias_kind":"pith_short_16","alias_value":"I5MAQ3YUOT5TQJOR","created_at":"2026-07-05T11:14:03.831369+00:00"},{"alias_kind":"pith_short_8","alias_value":"I5MAQ3YU","created_at":"2026-07-05T11:14:03.831369+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/I5MAQ3YUOT5TQJORUYKHXKFOXK","json":"https://pith.science/pith/I5MAQ3YUOT5TQJORUYKHXKFOXK.json","graph_json":"https://pith.science/api/pith-number/I5MAQ3YUOT5TQJORUYKHXKFOXK/graph.json","events_json":"https://pith.science/api/pith-number/I5MAQ3YUOT5TQJORUYKHXKFOXK/events.json","paper":"https://pith.science/paper/I5MAQ3YU"},"agent_actions":{"view_html":"https://pith.science/pith/I5MAQ3YUOT5TQJORUYKHXKFOXK","download_json":"https://pith.science/pith/I5MAQ3YUOT5TQJORUYKHXKFOXK.json","view_paper":"https://pith.science/paper/I5MAQ3YU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.08662&json=true","fetch_graph":"https://pith.science/api/pith-number/I5MAQ3YUOT5TQJORUYKHXKFOXK/graph.json","fetch_events":"https://pith.science/api/pith-number/I5MAQ3YUOT5TQJORUYKHXKFOXK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/I5MAQ3YUOT5TQJORUYKHXKFOXK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/I5MAQ3YUOT5TQJORUYKHXKFOXK/action/storage_attestation","attest_author":"https://pith.science/pith/I5MAQ3YUOT5TQJORUYKHXKFOXK/action/author_attestation","sign_citation":"https://pith.science/pith/I5MAQ3YUOT5TQJORUYKHXKFOXK/action/citation_signature","submit_replication":"https://pith.science/pith/I5MAQ3YUOT5TQJORUYKHXKFOXK/action/replication_record"}},"created_at":"2026-07-05T11:14:03.831369+00:00","updated_at":"2026-07-05T11:14:03.831369+00:00"}