Paper Citation Record · LEDGER

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation

As of 7 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2506.18670.

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

pith.paper-citation-record.v1
2506.18670 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:20:35.039153Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

33 of 33 outbound references displayed

verified exact0
verified fuzzy8
unresolved24
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 79fa8d19-cdb3-4c89-9a72-22901181c182 · outbound

This paper cites Umass at trec 2004: Novelty and hard.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Umass at trec 2004: Novelty and hard

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:37.691985Z

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 4e1cdd66-c5b3-4ea9-b701-efbbb5f65af7 · outbound

This paper cites The snowflake elastic data warehouse.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation The snowflake elastic data warehouse

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:37.524777Z

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 20186bc2-508f-4606-b4c1-13dd498c8fd2 · outbound

This paper cites Dense passage retrieval for open-domain question answering.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Dense passage retrieval for open-domain question answering

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:37.325696Z

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 b23ba221-dd4a-4a6a-8638-3338fc4540eb · outbound

This paper cites Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:33.318382Z

Source-reported events for the cited work

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Observation 7538546d-82ba-4388-8348-3d50c4e685e2 · outbound

This paper cites Internet-augmented language models through few-shot prompting for open-domain question answering.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Internet-augmented language models through few-shot prompting for open-domain question answering

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:33.395421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e65e2d00-a61d-4f3e-833f-10908d9bc588 · outbound

This paper cites Query rewriting in retrieval- augmented large language models.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Query rewriting in retrieval- augmented large language models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:36.834810Z

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 05151d47-7f33-407c-abc0-81e1de0a52c3 · outbound

This paper cites RaFe: Ranking Feedback Improves Query Rewriting for RAG.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation RaFe: Ranking Feedback Improves Query Rewriting for RAG

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:33.552216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87fe10bd-61ec-4bea-a7b7-0679ec8b0b70 · outbound

This paper cites Measuring and Narrowing the Compositionality Gap in Language Models.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Measuring and Narrowing the Compositionality Gap in Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:33.669571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d73d76e-2742-4d23-967f-7d90ae614c00 · outbound

This paper cites Large Language Models are Strong Zero-Shot Retriever.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Large Language Models are Strong Zero-Shot Retriever

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:33.901661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d5aacc5-daf4-4d1a-8017-b0d10ac2db09 · outbound

This paper cites HybridFlow: A Flexible and Efficient RLHF Framework.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation HybridFlow: A Flexible and Efficient RLHF Framework

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:33.950971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab97999b-f31d-4919-a89e-6b1423ec8dcc · outbound

This paper cites REPLUG: Retrieval-Augmented Black-Box Language Models.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation REPLUG: Retrieval-Augmented Black-Box Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:34.022956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 972397bb-0e2d-4add-b463-bb80b7c22ca2 · outbound

This paper cites Query2doc: Query Expansion with Large Language Models.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Query2doc: Query Expansion with Large Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:34.396029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b4b9822-f99f-4585-801e-c208140af0ec · outbound

This paper cites Multilingual E5 Text Embeddings: A Technical Report.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Multilingual E5 Text Embeddings: A Technical Report

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:34.478229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8acf5575-aed1-41f6-b98e-495124b08d58 · outbound

This paper cites Query expansion with freebase.Proceedings of the 2015 International Conference on The Theory of Information Retrieval,.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Query expansion with freebase.Proceedings of the 2015 International Conference on The Theory of Information Retrieval,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:36.290421Z

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 55e68d54-7f8a-4167-bb2e-bed4084c9bad · outbound

This paper cites Enhancing Conversational Search: Large Language Model-Aided Informative Query Rewriting.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Enhancing Conversational Search: Large Language Model-Aided Informative Query Rewriting

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:34.734211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85f834c6-fc70-45e6-8e58-6505313c2126 · outbound

This paper cites The best results are bolded, and other top-three results are underlined.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation The best results are bolded, and other top-three results are underlined

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:35.862890Z

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 ac510c28-a231-4374-afb1-860b06c7d40e · outbound

This paper cites an unresolved cited work.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Unresolved cited work

Reference 34

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T23:20:35.572703Z

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 b94e965a-0b18-4840-a46d-89f518f9e607 · outbound

This paper cites Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,

Reference 1982

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:32.637146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a151714-9eed-4091-a757-208583949cb7 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Proximal Policy Optimization Algorithms

Reference 1988

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:33.836645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 485abd80-0eaa-4066-918c-5f70f1482e8f · outbound

This paper cites Learning to summarize from human feedback.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Learning to summarize from human feedback

Reference 2001

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:34.126560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48056f53-88b4-4252-9b74-57141a8c9a6a · outbound

This paper cites Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely

Reference 2008

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:34.827663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a58daef-afd3-4083-806f-55bfefd012a9 · outbound

This paper cites Hamilton, Chris Dyer, and Dani Yogatama.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Hamilton, Chris Dyer, and Dani Yogatama

Reference 2009

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:36.544748Z

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 018011c7-66aa-410b-97a7-4c2ebbe1bb2c · outbound

This paper cites BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

Reference 2010

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:34.235230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dec8fa1e-815e-4e34-af85-c3f40b074e0d · outbound

This paper cites The Faiss library.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation The Faiss library

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:32.777818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af19faba-db54-47d0-b29d-51a38a178c0c · outbound

This paper cites Deep reinforcement learning from human preferences.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Deep reinforcement learning from human preferences

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:32.682670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4310ec17-a2b9-458f-8c47-416bd189990a · outbound

This paper cites Training language models to follow instructions with human feedback.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Training language models to follow instructions with human feedback

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:33.608260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f5d099a-4029-4665-a511-63766b0cc725 · outbound

This paper cites You only need one model for open-domain question answering.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation You only need one model for open-domain question answering

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:37.075468Z

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 5487c94a-887e-4904-a508-d404b5b6fd49 · outbound

This paper cites Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:32.987960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2d4a71f-ae04-4fdb-a072-61723c9d16ef · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:34.331047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74867ca8-411d-4ef4-a9c4-a300bbb92cb6 · outbound

This paper cites DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:33.163275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7b57add-abc9-42b3-b093-f1a095e911ca · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:32.914472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b3849b0-f77e-42db-ad16-6dc09ccd52a0 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:32.857634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8150b4c-7826-4b4e-b19d-35af7d4f7ec9 · outbound

This paper cites REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization.

Harnessing the Power of Reinforcement Learning for Language-Model-Based Information Retriever via Query-Document Co-Augmentation REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:33.108723Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.