Paper Citation Record · LEDGER

Enhancing Q&A Text Retrieval with Ranking Models: Benchmarking, fine-tuning and deploying Rerankers for RAG

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2409.07691.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2409.07691 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:18:34.757513Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2a473cc8-6605-417a-a355-f7d936d027d5 · inbound

LLMs as Better Recommenders with Natural Language Collaborative Signals: A Self-Assessing Retrieval Approach cites this paper.

LLMs as Better Recommenders with Natural Language Collaborative Signals: A Self-Assessing Retrieval Approach Enhancing Q&A Text Retrieval with Ranking Models: Benchmarking, fine-tuning and deploying Rerankers for RAG

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:18:34.757513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89d765ea-ee59-427c-b9de-c03965870a06 · inbound

MM-R5: MultiModal Reasoning-Enhanced ReRanker via Reinforcement Learning for Document Retrieval cites this paper.

MM-R5: MultiModal Reasoning-Enhanced ReRanker via Reinforcement Learning for Document Retrieval Enhancing Q&A Text Retrieval with Ranking Models: Benchmarking, fine-tuning and deploying Rerankers for RAG

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T00:57:03.153676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87db0643-0f14-48fc-85c7-25d800dcda00 · inbound

Understand and Accelerate Memory Processing Pipeline for Large Language Model Inference cites this paper.

Understand and Accelerate Memory Processing Pipeline for Large Language Model Inference Enhancing Q&A Text Retrieval with Ranking Models: Benchmarking, fine-tuning and deploying Rerankers for RAG

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-14T00:28:29.937045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 49708029-57ac-48d7-80a4-e28da60cb43e · inbound

Evaluating Multi-Hop Reasoning in RAG Systems: A Comparison of LLM-Based Retriever Evaluation Strategies cites this paper.

Evaluating Multi-Hop Reasoning in RAG Systems: A Comparison of LLM-Based Retriever Evaluation Strategies Enhancing Q&A Text Retrieval with Ranking Models: Benchmarking, fine-tuning and deploying Rerankers for RAG

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-10T04:04:47.616998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cc802f78-3a0a-466f-9988-3084f5e2f6e6 · inbound

A Reproducibility Study of Metacognitive Retrieval-Augmented Generation cites this paper.

A Reproducibility Study of Metacognitive Retrieval-Augmented Generation Enhancing Q&A Text Retrieval with Ranking Models: Benchmarking, fine-tuning and deploying Rerankers for RAG

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:36:09.197026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.