{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:FCGF5R3H3ASYXDLV7RDRBYSDCJ","short_pith_number":"pith:FCGF5R3H","canonical_record":{"source":{"id":"2505.19284","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-05-25T19:29:27Z","cross_cats_sorted":[],"title_canon_sha256":"339805574fc8d941660f7db17ed3d95893a8b4566ce3afbf3a44a31ea08cefaf","abstract_canon_sha256":"f16898a4bc9e4f668cf59d78e3cd5931e98c2f47fb3418efadd360237ce2e7ad"},"schema_version":"1.0"},"canonical_sha256":"288c5ec767d8258b8d75fc4710e2431257cf2d45b44218ffc86d02a38da140d6","source":{"kind":"arxiv","id":"2505.19284","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.19284","created_at":"2026-07-05T11:09:27Z"},{"alias_kind":"arxiv_version","alias_value":"2505.19284v1","created_at":"2026-07-05T11:09:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.19284","created_at":"2026-07-05T11:09:27Z"},{"alias_kind":"pith_short_12","alias_value":"FCGF5R3H3ASY","created_at":"2026-07-05T11:09:27Z"},{"alias_kind":"pith_short_16","alias_value":"FCGF5R3H3ASYXDLV","created_at":"2026-07-05T11:09:27Z"},{"alias_kind":"pith_short_8","alias_value":"FCGF5R3H","created_at":"2026-07-05T11:09:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:FCGF5R3H3ASYXDLV7RDRBYSDCJ","target":"record","payload":{"canonical_record":{"source":{"id":"2505.19284","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-05-25T19:29:27Z","cross_cats_sorted":[],"title_canon_sha256":"339805574fc8d941660f7db17ed3d95893a8b4566ce3afbf3a44a31ea08cefaf","abstract_canon_sha256":"f16898a4bc9e4f668cf59d78e3cd5931e98c2f47fb3418efadd360237ce2e7ad"},"schema_version":"1.0"},"canonical_sha256":"288c5ec767d8258b8d75fc4710e2431257cf2d45b44218ffc86d02a38da140d6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:09:27.621364Z","signature_b64":"GtEU/2GJX72uTC+b6wnX31M+oJFrsmhaWpiB9cWQnv22PZfeJUzx6pKSill2wNX4tfTwhfDcDtG7Bxo+KvfFDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"288c5ec767d8258b8d75fc4710e2431257cf2d45b44218ffc86d02a38da140d6","last_reissued_at":"2026-07-05T11:09:27.620860Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:09:27.620860Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.19284","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:09:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rVRHvIdbTWfRg9qD6iBMY0ChnZJU2n8yE40KpJ3qcpPbScNS27mW0qoW5gv/CBMhGGr2oVoaBDK5cLcq6FKVBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T09:58:03.165131Z"},"content_sha256":"9fffa5e98baae8971cc7c3ffbb216ff4bc01c316771518743be644e05457e00e","schema_version":"1.0","event_id":"sha256:9fffa5e98baae8971cc7c3ffbb216ff4bc01c316771518743be644e05457e00e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:FCGF5R3H3ASYXDLV7RDRBYSDCJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RankLLM: A Python Package for Reranking with LLMs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Andre Slavescu, Andrew Xu, Jasper Xian, Jimmy Lin, Ronak Pradeep, Ryan Nguyen, Sahel Sharifymoghaddam, Yidi Chen, Yilin Zhang, Zijian Chen","submitted_at":"2025-05-25T19:29:27Z","abstract_excerpt":"The adoption of large language models (LLMs) as rerankers in multi-stage retrieval systems has gained significant traction in academia and industry. These models refine a candidate list of retrieved documents, often through carefully designed prompts, and are typically used in applications built on retrieval-augmented generation (RAG). This paper introduces RankLLM, an open-source Python package for reranking that is modular, highly configurable, and supports both proprietary and open-source LLMs in customized reranking workflows. To improve usability, RankLLM features optional integration wit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.19284","kind":"arxiv","version":1},"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/2505.19284/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":"2026-07-05T11:09:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GayyT5KmLb9P+RU/YbjWknJ+kqsQ0+2ojLHGOEFBXo8SG8JwU9JevNFhwxTZFvzxmCBrsVyhh+FtHS5YSxs5Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T09:58:03.165524Z"},"content_sha256":"58143c4b7c5cf045d56794ed7ce6b187a14e25ef30464d3116a931eeca5e30fd","schema_version":"1.0","event_id":"sha256:58143c4b7c5cf045d56794ed7ce6b187a14e25ef30464d3116a931eeca5e30fd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FCGF5R3H3ASYXDLV7RDRBYSDCJ/bundle.json","state_url":"https://pith.science/pith/FCGF5R3H3ASYXDLV7RDRBYSDCJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FCGF5R3H3ASYXDLV7RDRBYSDCJ/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":"2026-07-06T09:58:03Z","links":{"resolver":"https://pith.science/pith/FCGF5R3H3ASYXDLV7RDRBYSDCJ","bundle":"https://pith.science/pith/FCGF5R3H3ASYXDLV7RDRBYSDCJ/bundle.json","state":"https://pith.science/pith/FCGF5R3H3ASYXDLV7RDRBYSDCJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FCGF5R3H3ASYXDLV7RDRBYSDCJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:FCGF5R3H3ASYXDLV7RDRBYSDCJ","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":"f16898a4bc9e4f668cf59d78e3cd5931e98c2f47fb3418efadd360237ce2e7ad","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-05-25T19:29:27Z","title_canon_sha256":"339805574fc8d941660f7db17ed3d95893a8b4566ce3afbf3a44a31ea08cefaf"},"schema_version":"1.0","source":{"id":"2505.19284","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.19284","created_at":"2026-07-05T11:09:27Z"},{"alias_kind":"arxiv_version","alias_value":"2505.19284v1","created_at":"2026-07-05T11:09:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.19284","created_at":"2026-07-05T11:09:27Z"},{"alias_kind":"pith_short_12","alias_value":"FCGF5R3H3ASY","created_at":"2026-07-05T11:09:27Z"},{"alias_kind":"pith_short_16","alias_value":"FCGF5R3H3ASYXDLV","created_at":"2026-07-05T11:09:27Z"},{"alias_kind":"pith_short_8","alias_value":"FCGF5R3H","created_at":"2026-07-05T11:09:27Z"}],"graph_snapshots":[{"event_id":"sha256:58143c4b7c5cf045d56794ed7ce6b187a14e25ef30464d3116a931eeca5e30fd","target":"graph","created_at":"2026-07-05T11:09:27Z","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/2505.19284/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The adoption of large language models (LLMs) as rerankers in multi-stage retrieval systems has gained significant traction in academia and industry. These models refine a candidate list of retrieved documents, often through carefully designed prompts, and are typically used in applications built on retrieval-augmented generation (RAG). This paper introduces RankLLM, an open-source Python package for reranking that is modular, highly configurable, and supports both proprietary and open-source LLMs in customized reranking workflows. To improve usability, RankLLM features optional integration wit","authors_text":"Andre Slavescu, Andrew Xu, Jasper Xian, Jimmy Lin, Ronak Pradeep, Ryan Nguyen, Sahel Sharifymoghaddam, Yidi Chen, Yilin Zhang, Zijian Chen","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-05-25T19:29:27Z","title":"RankLLM: A Python Package for Reranking with LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.19284","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":"sha256:9fffa5e98baae8971cc7c3ffbb216ff4bc01c316771518743be644e05457e00e","target":"record","created_at":"2026-07-05T11:09:27Z","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":"f16898a4bc9e4f668cf59d78e3cd5931e98c2f47fb3418efadd360237ce2e7ad","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2025-05-25T19:29:27Z","title_canon_sha256":"339805574fc8d941660f7db17ed3d95893a8b4566ce3afbf3a44a31ea08cefaf"},"schema_version":"1.0","source":{"id":"2505.19284","kind":"arxiv","version":1}},"canonical_sha256":"288c5ec767d8258b8d75fc4710e2431257cf2d45b44218ffc86d02a38da140d6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"288c5ec767d8258b8d75fc4710e2431257cf2d45b44218ffc86d02a38da140d6","first_computed_at":"2026-07-05T11:09:27.620860Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:09:27.620860Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GtEU/2GJX72uTC+b6wnX31M+oJFrsmhaWpiB9cWQnv22PZfeJUzx6pKSill2wNX4tfTwhfDcDtG7Bxo+KvfFDw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:09:27.621364Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.19284","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9fffa5e98baae8971cc7c3ffbb216ff4bc01c316771518743be644e05457e00e","sha256:58143c4b7c5cf045d56794ed7ce6b187a14e25ef30464d3116a931eeca5e30fd"],"state_sha256":"942c055e8270f8e4cb7ae870e3dd35a6fa22b8c7efd45aba9300f0393793d995"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wdfYBlcM+/3VHsvEoizQet4PmQSOgWMr3CxnRpTTkN+ipnuwDJWhzAAuwLqeumbCeLcSdVvm/+PnDBcF9QFhBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T09:58:03.167770Z","bundle_sha256":"73756fb865c8ddc4c399bba1b430a6f7897e0614e0822bd9b85970b8d19d6a59"}}