{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:FYXSAIQLQ4KJCFAM257FLLMI2F","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":"c77b064c3efe3c5808fce6279329008c05c8b60c551cc474a43da566d31674be","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-28T07:30:05Z","title_canon_sha256":"677280ee5cac6f91027fb7d65b911f329050a512f2d71b9b161b2235000f9679"},"schema_version":"1.0","source":{"id":"2412.20061","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.20061","created_at":"2026-07-05T10:01:18Z"},{"alias_kind":"arxiv_version","alias_value":"2412.20061v2","created_at":"2026-07-05T10:01:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.20061","created_at":"2026-07-05T10:01:18Z"},{"alias_kind":"pith_short_12","alias_value":"FYXSAIQLQ4KJ","created_at":"2026-07-05T10:01:18Z"},{"alias_kind":"pith_short_16","alias_value":"FYXSAIQLQ4KJCFAM","created_at":"2026-07-05T10:01:18Z"},{"alias_kind":"pith_short_8","alias_value":"FYXSAIQL","created_at":"2026-07-05T10:01:18Z"}],"graph_snapshots":[{"event_id":"sha256:28ddad15eca22d3e3cee9110b27aadea8be42861031ab917b492ef505953ac6a","target":"graph","created_at":"2026-07-05T10:01:18Z","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/2412.20061/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have demonstrated significant effectiveness across various NLP tasks, including text ranking. This study assesses the performance of large language models (LLMs) in listwise reranking for limited-resource African languages. We compare proprietary models RankGPT3.5, Rank4o-mini, RankGPTo1-mini and RankClaude-sonnet in cross-lingual contexts. Results indicate that these LLMs significantly outperform traditional baseline methods such as BM25-DT in most evaluation metrics, particularly in nDCG@10 and MRR@100. These findings highlight the potential of LLMs in enhancing ","authors_text":"Chuanqi Shi, Hang Zhang, Lun Wang, Shaoshuai Du, Yanxin Shen, Yixian Shen, Yiyi Tao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-28T07:30:05Z","title":"Comparative Analysis of Listwise Reranking with Large Language Models in Limited-Resource Language Contexts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.20061","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:b96d7e7701e85e0302bb3f6b831279d7effec217b45c1b7a7b9227b4e5cc3343","target":"record","created_at":"2026-07-05T10:01:18Z","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":"c77b064c3efe3c5808fce6279329008c05c8b60c551cc474a43da566d31674be","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-28T07:30:05Z","title_canon_sha256":"677280ee5cac6f91027fb7d65b911f329050a512f2d71b9b161b2235000f9679"},"schema_version":"1.0","source":{"id":"2412.20061","kind":"arxiv","version":2}},"canonical_sha256":"2e2f20220b871491140cd77e55ad88d17dc5c79e0a03156f9202ab67152de69f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2e2f20220b871491140cd77e55ad88d17dc5c79e0a03156f9202ab67152de69f","first_computed_at":"2026-07-05T10:01:18.876223Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:01:18.876223Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6dAWqa/CxNWCrZk3cZXKxjD8FWW6+pn4dys4bQkZblVK2H/pyPtGskZekAfwl9+8e5LaYD2EdZyLF0T5onDbCg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:01:18.876677Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.20061","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b96d7e7701e85e0302bb3f6b831279d7effec217b45c1b7a7b9227b4e5cc3343","sha256:28ddad15eca22d3e3cee9110b27aadea8be42861031ab917b492ef505953ac6a"],"state_sha256":"dd643f389507c000f5c706c4a833df522cd8fa5887207ac3e76320d923ab3874"}