{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:YANYORNQVXZEDXNC32LLBZAQS3","short_pith_number":"pith:YANYORNQ","canonical_record":{"source":{"id":"2410.18097","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-10-08T11:28:06Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"cae224332b0cc1307ce43520095a17ef0d218cf80a8cd6958ecad9dfc235d6dc","abstract_canon_sha256":"8d4118ed5d68380cfd2e343ec336c633bcf1d53e8772a54d8adcbfa3129f850d"},"schema_version":"1.0"},"canonical_sha256":"c01b8745b0adf241dda2de96b0e41096e047d4bdfb7596fd32a2954b8f7a0dc8","source":{"kind":"arxiv","id":"2410.18097","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.18097","created_at":"2026-07-05T09:38:31Z"},{"alias_kind":"arxiv_version","alias_value":"2410.18097v3","created_at":"2026-07-05T09:38:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.18097","created_at":"2026-07-05T09:38:31Z"},{"alias_kind":"pith_short_12","alias_value":"YANYORNQVXZE","created_at":"2026-07-05T09:38:31Z"},{"alias_kind":"pith_short_16","alias_value":"YANYORNQVXZEDXNC","created_at":"2026-07-05T09:38:31Z"},{"alias_kind":"pith_short_8","alias_value":"YANYORNQ","created_at":"2026-07-05T09:38:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:YANYORNQVXZEDXNC32LLBZAQS3","target":"record","payload":{"canonical_record":{"source":{"id":"2410.18097","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-10-08T11:28:06Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"cae224332b0cc1307ce43520095a17ef0d218cf80a8cd6958ecad9dfc235d6dc","abstract_canon_sha256":"8d4118ed5d68380cfd2e343ec336c633bcf1d53e8772a54d8adcbfa3129f850d"},"schema_version":"1.0"},"canonical_sha256":"c01b8745b0adf241dda2de96b0e41096e047d4bdfb7596fd32a2954b8f7a0dc8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:38:31.368381Z","signature_b64":"xNXqX2ck5CGkWbJHs6yJ+2U/CGgXn/rKDtcI+22de84MxwvNPhFhd+yjfA8c69XVZxY2wrbE6VBH3q03aWckBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c01b8745b0adf241dda2de96b0e41096e047d4bdfb7596fd32a2954b8f7a0dc8","last_reissued_at":"2026-07-05T09:38:31.367953Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:38:31.367953Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.18097","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:38:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7VSXDmPPBu7k2NtrDJWw1uMs945++CmLjkkMNWYU/K1HVR9Mo2GCmqLwRubn50fWtLPc9iiLnr2drb+1KPKcBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T14:25:56.519614Z"},"content_sha256":"262b446123eaf6827f0caa558cd54d7ea48546e4b28631f13fc31a1096c1509b","schema_version":"1.0","event_id":"sha256:262b446123eaf6827f0caa558cd54d7ea48546e4b28631f13fc31a1096c1509b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:YANYORNQVXZEDXNC32LLBZAQS3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RRADistill: Distilling LLMs' Passage Ranking Ability for Long-Tail Queries Document Re-Ranking on a Search Engine","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.IR","authors_text":"Gyohee Nam, Gyu-Hwung Cho, Haeyu Jeong, Inchang Jeong, Jaeho Choi, Jungmin Kong, Keunchan Park, Nayoung Choi, Saehun Kim, Sarah Cho, Sunghoon Han, Wonil Yang, Youngjune Lee","submitted_at":"2024-10-08T11:28:06Z","abstract_excerpt":"Large Language Models (LLMs) excel at understanding the semantic relationships between queries and documents, even with lengthy and complex long-tail queries. These queries are challenging for feedback-based rankings due to sparse user engagement and limited feedback, making LLMs' ranking ability highly valuable. However, the large size and slow inference of LLMs necessitate the development of smaller, more efficient models (sLLMs). Recently, integrating ranking label generation into distillation techniques has become crucial, but existing methods underutilize LLMs' capabilities and are cumber"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.18097","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/2410.18097/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:38:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mJXVOF4tlFOiek27E97vlDBBli1+2KqVdPbjOpaRtrAIe4Ld9lPvDsqnHkWpOXtwJUJgHzlotdHA4bgioYpnBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T14:25:56.520122Z"},"content_sha256":"65f72193a6c9d5efa70da68d1d1e03d14d648683640be7afdff4a5f2e89901e9","schema_version":"1.0","event_id":"sha256:65f72193a6c9d5efa70da68d1d1e03d14d648683640be7afdff4a5f2e89901e9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YANYORNQVXZEDXNC32LLBZAQS3/bundle.json","state_url":"https://pith.science/pith/YANYORNQVXZEDXNC32LLBZAQS3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YANYORNQVXZEDXNC32LLBZAQS3/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-05T14:25:56Z","links":{"resolver":"https://pith.science/pith/YANYORNQVXZEDXNC32LLBZAQS3","bundle":"https://pith.science/pith/YANYORNQVXZEDXNC32LLBZAQS3/bundle.json","state":"https://pith.science/pith/YANYORNQVXZEDXNC32LLBZAQS3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YANYORNQVXZEDXNC32LLBZAQS3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:YANYORNQVXZEDXNC32LLBZAQS3","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":"8d4118ed5d68380cfd2e343ec336c633bcf1d53e8772a54d8adcbfa3129f850d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-10-08T11:28:06Z","title_canon_sha256":"cae224332b0cc1307ce43520095a17ef0d218cf80a8cd6958ecad9dfc235d6dc"},"schema_version":"1.0","source":{"id":"2410.18097","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.18097","created_at":"2026-07-05T09:38:31Z"},{"alias_kind":"arxiv_version","alias_value":"2410.18097v3","created_at":"2026-07-05T09:38:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.18097","created_at":"2026-07-05T09:38:31Z"},{"alias_kind":"pith_short_12","alias_value":"YANYORNQVXZE","created_at":"2026-07-05T09:38:31Z"},{"alias_kind":"pith_short_16","alias_value":"YANYORNQVXZEDXNC","created_at":"2026-07-05T09:38:31Z"},{"alias_kind":"pith_short_8","alias_value":"YANYORNQ","created_at":"2026-07-05T09:38:31Z"}],"graph_snapshots":[{"event_id":"sha256:65f72193a6c9d5efa70da68d1d1e03d14d648683640be7afdff4a5f2e89901e9","target":"graph","created_at":"2026-07-05T09:38:31Z","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/2410.18097/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) excel at understanding the semantic relationships between queries and documents, even with lengthy and complex long-tail queries. These queries are challenging for feedback-based rankings due to sparse user engagement and limited feedback, making LLMs' ranking ability highly valuable. However, the large size and slow inference of LLMs necessitate the development of smaller, more efficient models (sLLMs). Recently, integrating ranking label generation into distillation techniques has become crucial, but existing methods underutilize LLMs' capabilities and are cumber","authors_text":"Gyohee Nam, Gyu-Hwung Cho, Haeyu Jeong, Inchang Jeong, Jaeho Choi, Jungmin Kong, Keunchan Park, Nayoung Choi, Saehun Kim, Sarah Cho, Sunghoon Han, Wonil Yang, Youngjune Lee","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-10-08T11:28:06Z","title":"RRADistill: Distilling LLMs' Passage Ranking Ability for Long-Tail Queries Document Re-Ranking on a Search Engine"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.18097","kind":"arxiv","version":3},"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":"sha256:262b446123eaf6827f0caa558cd54d7ea48546e4b28631f13fc31a1096c1509b","target":"record","created_at":"2026-07-05T09:38:31Z","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":"8d4118ed5d68380cfd2e343ec336c633bcf1d53e8772a54d8adcbfa3129f850d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2024-10-08T11:28:06Z","title_canon_sha256":"cae224332b0cc1307ce43520095a17ef0d218cf80a8cd6958ecad9dfc235d6dc"},"schema_version":"1.0","source":{"id":"2410.18097","kind":"arxiv","version":3}},"canonical_sha256":"c01b8745b0adf241dda2de96b0e41096e047d4bdfb7596fd32a2954b8f7a0dc8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c01b8745b0adf241dda2de96b0e41096e047d4bdfb7596fd32a2954b8f7a0dc8","first_computed_at":"2026-07-05T09:38:31.367953Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:38:31.367953Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xNXqX2ck5CGkWbJHs6yJ+2U/CGgXn/rKDtcI+22de84MxwvNPhFhd+yjfA8c69XVZxY2wrbE6VBH3q03aWckBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:38:31.368381Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.18097","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:262b446123eaf6827f0caa558cd54d7ea48546e4b28631f13fc31a1096c1509b","sha256:65f72193a6c9d5efa70da68d1d1e03d14d648683640be7afdff4a5f2e89901e9"],"state_sha256":"730b05aa0dfad3ddb1524ca60f6484019ce8f1cfba6dfd98e341e3660c457b49"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QoB8xuZxPPD0b5IP5dc7XfWkxmYrYYtM8BHIEV04mtrbMgcuLTcMfWls6dNhNBei6BEDOgE+Ly/moP2Eh28ACw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T14:25:56.525079Z","bundle_sha256":"fbe2ebd591c7f8af54daac0d67011bee13cbb99379885606e27965956b9c6ca8"}}