{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:5BHPE63YQFSXYID4TZBBTNM7A6","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":"b8449005ef507b231219ac8cd79d73c8a0ee4347e1d048220a17c65f8d2be5ee","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-26T20:12:24Z","title_canon_sha256":"1ae447cf0308e35215a81c2f2b60dfa16d46dc66d1cd2964b856384eeeb1f852"},"schema_version":"1.0","source":{"id":"2406.18740","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.18740","created_at":"2026-07-05T08:37:25Z"},{"alias_kind":"arxiv_version","alias_value":"2406.18740v1","created_at":"2026-07-05T08:37:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.18740","created_at":"2026-07-05T08:37:25Z"},{"alias_kind":"pith_short_12","alias_value":"5BHPE63YQFSX","created_at":"2026-07-05T08:37:25Z"},{"alias_kind":"pith_short_16","alias_value":"5BHPE63YQFSXYID4","created_at":"2026-07-05T08:37:25Z"},{"alias_kind":"pith_short_8","alias_value":"5BHPE63Y","created_at":"2026-07-05T08:37:25Z"}],"graph_snapshots":[{"event_id":"sha256:70caa7d199a4e1c6e3f8e77891adcd77b6f2487d923fd2e568dd4d6c06510e2a","target":"graph","created_at":"2026-07-05T08:37:25Z","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/2406.18740/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have been revolutionizing a myriad of natural language processing tasks with their diverse zero-shot capabilities. Indeed, existing work has shown that LLMs can be used to great effect for many tasks, such as information retrieval (IR), and passage ranking. However, current state-of-the-art results heavily lean on the capabilities of the LLM being used. Currently, proprietary, and very large LLMs such as GPT-4 are the highest performing passage re-rankers. Hence, users without the resources to leverage top of the line LLMs, or ones that are closed source, are at a ","authors_text":"Baharan Nouriinanloo, Maxime Lamothe","cross_cats":["cs.IR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-26T20:12:24Z","title":"Re-Ranking Step by Step: Investigating Pre-Filtering for Re-Ranking with Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.18740","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:bf1c8df891f4f355a2fa23fb56e7cb1d10352bb29067ee78f4adfb086484bbc0","target":"record","created_at":"2026-07-05T08:37:25Z","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":"b8449005ef507b231219ac8cd79d73c8a0ee4347e1d048220a17c65f8d2be5ee","cross_cats_sorted":["cs.IR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-06-26T20:12:24Z","title_canon_sha256":"1ae447cf0308e35215a81c2f2b60dfa16d46dc66d1cd2964b856384eeeb1f852"},"schema_version":"1.0","source":{"id":"2406.18740","kind":"arxiv","version":1}},"canonical_sha256":"e84ef27b7881657c207c9e4219b59f07ad1269ce8173351c664ddc0987dd636e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e84ef27b7881657c207c9e4219b59f07ad1269ce8173351c664ddc0987dd636e","first_computed_at":"2026-07-05T08:37:25.133788Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:37:25.133788Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5s+Rgvz5mTFTaPELQTLjg/ay3wKIM91wX5BObPfahAJIjM4W0H4kzs8/OUlwT3vJgTCKKOUTz3TKx1VLnyhaDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:37:25.134242Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.18740","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bf1c8df891f4f355a2fa23fb56e7cb1d10352bb29067ee78f4adfb086484bbc0","sha256:70caa7d199a4e1c6e3f8e77891adcd77b6f2487d923fd2e568dd4d6c06510e2a"],"state_sha256":"c60c03a11dac728b75c36fb06a8e2b2e29969c84c5ebab04bc05bef8775e6dd7"}