Paper Citation Record · LEDGER

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation

As of 8 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2510.10448.

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

pith.paper-citation-record.v1
2510.10448 v2

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T10:20:22.439184Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

39 of 39 outbound references displayed

verified exact0
verified fuzzy0
unresolved39
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5f957e78-257f-4429-badc-667afce5c5bb · outbound

This paper cites My action is not correct. Let me rethink.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation My action is not correct. Let me rethink

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:22.385906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59fdbd4b-ec6e-42b7-92bc-75332a118b4f · outbound

This paper cites ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:19.722719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffe7aa27-7a52-4fda-a4be-e5d0f1b2209d · outbound

This paper cites Group-in-Group Policy Optimization for LLM Agent Training.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Group-in-Group Policy Optimization for LLM Agent Training

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:19.992716Z

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Unavailable: canonical work link unavailable.

Observation 98d9ee38-f4a7-4127-94fe-90db91814af5 · outbound

This paper cites Towards an AI co-scientist.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Towards an AI co-scientist

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.054756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27153563-f7b3-4fd8-ad61-703ea5080f1d · outbound

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

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.093405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00db993a-9d15-497b-950c-8b9c59fd37b4 · outbound

This paper cites GPT-4o System Card.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation GPT-4o System Card

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.308668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd9e47c5-8ece-4b9a-9588-6696cc8585dd · outbound

This paper cites OpenAI o1 System Card.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation OpenAI o1 System Card

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.383751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa264529-929a-4f11-a60c-de63a1d9c193 · outbound

This paper cites FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.409475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9fe0967-cfc4-4a39-805b-4b68c40615c7 · outbound

This paper cites Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.487943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58b3d204-1be6-4e55-bc76-f0b5d42e6365 · outbound

This paper cites Measuring Faithfulness in Chain-of-Thought Reasoning.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Measuring Faithfulness in Chain-of-Thought Reasoning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.530862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 160634b6-9500-406e-9c74-42f4587095a0 · outbound

This paper cites an unresolved cited work.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Unresolved cited work

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.565412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 912ee801-22ae-4e4a-9bf6-fdf44984ef59 · outbound

This paper cites Search-o1: Agentic Search-Enhanced Large Reasoning Models.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Search-o1: Agentic Search-Enhanced Large Reasoning Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.607969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ced02cff-8651-4063-bb1f-c8668db71884 · outbound

This paper cites Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Koh, Mohit Iyyer, Luke Zettle- moyer, and Hannaneh Hajishirzi.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Koh, Mohit Iyyer, Luke Zettle- moyer, and Hannaneh Hajishirzi

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.655141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de9493ae-8ce4-42e8-816f-0331f87fb026 · outbound

This paper cites InProceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 12076–12100, Singa- pore.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation InProceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 12076–12100, Singa- pore

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.715123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98b65302-44eb-4653-8169-fb65d04ac0b2 · outbound

This paper cites InFindings of the Association for Computational Linguistics: EMNLP 2023, pages 5687–5711, Singa- pore.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation InFindings of the Association for Computational Linguistics: EMNLP 2023, pages 5687–5711, Singa- pore

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.794180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16dda218-0c1c-4bfa-8359-6013bddb1342 · outbound

This paper cites Proximal Policy Optimization Algorithms.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Proximal Policy Optimization Algorithms

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.828304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3aa84350-b31e-4d9f-bea5-389dcca3625b · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.866121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ac24b6c-f950-46fc-9d28-e2dc04ff33c6 · outbound

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

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation HybridFlow: A Flexible and Efficient RLHF Framework

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.918250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f794a16-c141-4569-aded-7da6f5002797 · outbound

This paper cites R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.951958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f25fbd1-4f95-44fc-8cd2-0267dda19230 · outbound

This paper cites DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.991380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 871a9da7-0447-46d5-88fa-04500cd9ba91 · outbound

This paper cites Fangyuan Xu, Weijia Shi, and Eunsol Choi.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Fangyuan Xu, Weijia Shi, and Eunsol Choi

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:21.247005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0457ae1a-ba93-4bd5-9f12-ac34666358f9 · outbound

This paper cites Zhichao Xu, Fengran Mo, Zhiqi Huang, Crystina Zhang, Puxuan Yu, Bei Wang, Jimmy Lin, and Vivek Sriku- mar.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Zhichao Xu, Fengran Mo, Zhiqi Huang, Crystina Zhang, Puxuan Yu, Bei Wang, Jimmy Lin, and Vivek Sriku- mar

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:21.498094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7783526-5f3a-4b8c-b85a-f27b22425fe8 · outbound

This paper cites Zhichao Xu, Jinghua Yan, Ashim Gupta, and Vivek Srikumar.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Zhichao Xu, Jinghua Yan, Ashim Gupta, and Vivek Srikumar

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:21.614925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd0b1541-dc48-4b73-81e1-d0b6dacf3449 · outbound

This paper cites InProceedings of the 10th Workshop on Representation Learning for NLP (RepL4NLP- 2025), pages 152–169, Albuquerque, NM.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation InProceedings of the 10th Workshop on Representation Learning for NLP (RepL4NLP- 2025), pages 152–169, Albuquerque, NM

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:21.723301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30463cbb-e397-447d-be30-0335a5e21255 · outbound

This paper cites Qwen2.5 Technical Report.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Qwen2.5 Technical Report

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:21.833302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb2653d4-df3e-4577-9746-d362290023b2 · outbound

This paper cites DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:22.087149Z

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Unavailable: canonical work link unavailable.

Observation e6688330-d6c0-4600-90f6-0b9970dd7e1d · outbound

This paper cites pre-training.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation pre-training

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:22.144702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a21f12b-af43-4127-81ae-9fab0aa76598 · outbound

This paper cites pre- training.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation pre- training

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:22.255943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b10942bc-9ce9-4250-bd62-cb2323b4a459 · outbound

This paper cites We retrieve top-5 passages (baseline: top-3).

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation We retrieve top-5 passages (baseline: top-3)

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:22.327168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95a766c7-27a9-41c4-a2b1-d1c576d12984 · outbound

This paper cites MS MARCO: A Human Generated MAchine Reading COmprehension Dataset.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation MS MARCO: A Human Generated MAchine Reading COmprehension Dataset

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:19.423374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bcb1687-7ccf-4490-8015-325ec21c551e · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.454565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8596431f-6ecd-4ebd-86bb-b7899c882d2a · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:21.927517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 947b0a6f-ab7f-450b-8bc3-4e3df23e2a1e · outbound

This paper cites Other baselines.Baseline methods in Table 1 include (1) prompting-based method: Direct Inference and Chain-of-Thought prompting (Wei et al., 2022).

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Other baselines.Baseline methods in Table 1 include (1) prompting-based method: Direct Inference and Chain-of-Thought prompting (Wei et al., 2022)

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:22.439184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b212c63b-0089-4474-8dcf-beccc91ad25c · outbound

This paper cites In Proceedings of the 2020 Conference on empirical methods in natural language processing (EMNLP), pages 3632–3645.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation In Proceedings of the 2020 Conference on empirical methods in natural language processing (EMNLP), pages 3632–3645

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:21.362817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54570b18-75e5-46c3-a50d-ea00eea39599 · outbound

This paper cites InProceedings of the 2021 Con- ference of the North American Chapter of the Asso- ciation for Computational Linguistics: Human Lan- guage Technologies, pages 4812–4829, Online.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation InProceedings of the 2021 Con- ference of the North American Chapter of the Asso- ciation for Computational Linguistics: Human Lan- guage Technologies, pages 4812–4829, Online

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.755937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 600f86d6-372e-4e90-a218-16a195e35c52 · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:21.101558Z

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Unavailable: canonical work link unavailable.

Observation ed3afefd-c49f-4d17-b960-e9a734514472 · outbound

This paper cites InProceedings of the 2023 Con- ference on Empirical Methods in Natural Language Processing, pages 3829–3846, Singapore.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation InProceedings of the 2023 Con- ference on Empirical Methods in Natural Language Processing, pages 3829–3846, Singapore

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:19.867472Z

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Unavailable: canonical work link unavailable.

Observation 7451616b-efa1-46ef-8f84-3791354101b6 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:20.207495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e15dbf24-155d-489d-ade0-7ef293cc7595 · outbound

This paper cites Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation.

RECON: Reasoning with Condensation for Efficient Retrieval-Augmented Generation Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-04T10:20:19.589725Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.