Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2502.02464.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:20:37.825619Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T20:58:45.165805Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation f38b646d-56cd-45af-8be3-60d91d0879fb · inbound
RankLLM: A Python Package for Reranking with LLMs cites this paper.
RankLLM: A Python Package for Reranking with LLMs Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:20:37.825619Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7ae4d162-8231-4a87-a6e6-8ee712c9b55c · inbound
Shifting from Ranking to Set Selection for Retrieval Augmented Generation cites this paper.
Shifting from Ranking to Set Selection for Retrieval Augmented Generation Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:57:33.556980Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation baebb7d7-c5d8-41ab-a705-e53d3873f122 · inbound
A Survey of Context Engineering for Large Language Models cites this paper.
A Survey of Context Engineering for Large Language Models Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T20:58:45.169008Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 7213cb4a-6e40-4fba-8859-f7306b185329 · inbound
How Good are LLM-based Rerankers? An Empirical Analysis of State-of-the-Art Reranking Models cites this paper.
How Good are LLM-based Rerankers? An Empirical Analysis of State-of-the-Art Reranking Models Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:15:15.232104Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ed7390e8-66eb-45bc-81fd-cec2425302e7 · inbound
Are LLM-Based Retrievers Worth Their Cost? An Empirical Study of Efficiency, Robustness, and Reasoning Overhead cites this paper.
Are LLM-Based Retrievers Worth Their Cost? An Empirical Study of Efficiency, Robustness, and Reasoning Overhead Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T17:23:02.659323Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 566acf1e-72ee-4ca2-8e55-9742ddc8a5ee · inbound
The LLM Effect on IR Benchmarks: A Meta-Analysis of Effectiveness, Baselines, and Contamination cites this paper.
The LLM Effect on IR Benchmarks: A Meta-Analysis of Effectiveness, Baselines, and Contamination Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T23:40:53.817109Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 56853ddb-6138-4d3b-8421-74d41a10124f · inbound
MARVEL: Multimodal Adaptive Reasoning-intensiVe Expand-rerank and retrievaL cites this paper.
MARVEL: Multimodal Adaptive Reasoning-intensiVe Expand-rerank and retrievaL Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T06:00:58.465205Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6be17e6e-45af-4204-a1ed-24540554a780 · inbound
BRIDGE: Multimodal-to-Text Retrieval via Reinforcement-Learned Query Alignment cites this paper.
BRIDGE: Multimodal-to-Text Retrieval via Reinforcement-Learned Query Alignment Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T06:41:56.606813Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation aaf6ba5b-8eaa-4961-92ba-3eb068d8cf5c · inbound
HIVE: Query, Hypothesize, Verify An LLM Framework for Multimodal Reasoning-Intensive Retrieval cites this paper.
HIVE: Query, Hypothesize, Verify An LLM Framework for Multimodal Reasoning-Intensive Retrieval Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T06:56:02.666429Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.