Paper Citation Record · LEDGER

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems

As of 8 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 2 inbound Pith citation observations for arXiv:2506.09200.

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

pith.paper-citation-record.v1
2506.09200 v2

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:57:29.372618Z

measured 43 of 43 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T07:26:08.285592Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:00:07.852965Z

Reference resolution

41 of 41 outbound references displayed

verified exact1
verified fuzzy21
unresolved18
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 238ab0f6-bd1b-496e-b009-ec4ee959ae9e · outbound

This paper cites Model context protocol, 2024.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Model context protocol, 2024

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:30.120157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ffcba122-21bc-4f14-9454-ea20b1986110 · outbound

This paper cites Semantic parsing on freebase from question-answer pairs.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Semantic parsing on freebase from question-answer pairs

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:30.104878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3b32ce8f-7933-49be-8863-2d838d7cd274 · outbound

This paper cites Enhancing RAG pipelines in Haystack: Introducing diversityranker and lostinthemiddleranker, 2023.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Enhancing RAG pipelines in Haystack: Introducing diversityranker and lostinthemiddleranker, 2023

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:30.090255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 55cd8d12-f987-41bd-880a-038119bae6f8 · outbound

This paper cites Brown, B.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Brown, B

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:30.075755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7518961f-e880-48d6-b716-906bfabed3be · outbound

This paper cites LangChain, October 2022.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems LangChain, October 2022

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:30.060537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2c10c92a-091c-4926-8fa2-0d902e301615 · outbound

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

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.223683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc43c61b-d933-459a-ad5d-599f69794c09 · outbound

This paper cites Suchanek, and Chlo´ e Clavel.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Suchanek, and Chlo´ e Clavel

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:30.044699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e762e009-30b4-40d4-bd03-32c9354ccc80 · outbound

This paper cites Deepseek-r1: Incentivizing rea- soning capability in llms via reinforcement learning,.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Deepseek-r1: Incentivizing rea- soning capability in llms via reinforcement learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:30.029885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0dc6de5e-cec3-4cfd-9065-67cdfa93339e · outbound

This paper cites Qlora: Efficient finetuning of quantized llms.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Qlora: Efficient finetuning of quantized llms

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.241641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d482aea0-eb6f-4f70-b692-b8e8ff6d1ee5 · outbound

This paper cites an unresolved cited work.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:57:30.004237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9c397beb-a378-480e-ab51-5948d5483965 · outbound

This paper cites LlamaIndex Networks, 11 2024.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems LlamaIndex Networks, 11 2024

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.990055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3b0d0dc8-8214-4553-83a7-6a77653d4ea8 · outbound

This paper cites A survey on rag meeting llms: To- wards retrieval-augmented large language models.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems A survey on rag meeting llms: To- wards retrieval-augmented large language models

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.976684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 033b0ab1-a15f-4150-9996-6b8239f113a8 · outbound

This paper cites Agent2agent (a2a) protocol, 2025.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Agent2agent (a2a) protocol, 2025

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.962597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 73eb354b-8d00-432a-bf1a-1df530416f3b · outbound

This paper cites The Llama 3 Herd of Models.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems The Llama 3 Herd of Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.267121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a564b1a-ff38-4c15-a433-9ee388289152 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Measuring Massive Multitask Language Understanding

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.271171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0ae1662-1950-48d8-9f79-7bf51e420441 · outbound

This paper cites A survey on hallucination in large lan- guage models: Principles, taxonomy, challenges, and open questions.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems A survey on hallucination in large lan- guage models: Principles, taxonomy, challenges, and open questions

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.275419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0976724b-6ea1-4c0b-904b-8937c8501c1c · outbound

This paper cites Atlas: Few-shot Learning with Retrieval Augmented Language Models.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Atlas: Few-shot Learning with Retrieval Augmented Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.279732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43642e97-5109-4abb-bab7-26075de3ae7b · outbound

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

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Dense passage retrieval for open-domain question answering

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.284233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55f4c23e-a259-4d40-aebc-354733fbfcf7 · outbound

This paper cites an unresolved cited work.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:57:29.948810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0cb2766e-3e38-4673-9273-261093bc11c2 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive NLP tasks.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Retrieval-augmented generation for knowledge-intensive NLP tasks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.935520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation eaa8141f-3f16-4a6d-b282-7af9b9387353 · outbound

This paper cites How to Train Your DRAGON: Diverse Augmentation Towards Generalizable Dense Retrieval.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems How to Train Your DRAGON: Diverse Augmentation Towards Generalizable Dense Retrieval

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.297001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61ff0f3a-c172-43c6-ae69-b74b177a38da · outbound

This paper cites Ra- dit: Retrieval-augmented dual instruction tuning.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Ra- dit: Retrieval-augmented dual instruction tuning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.922271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 16cf60c0-3fb5-4a8a-96d9-2fbe00339012 · outbound

This paper cites LlamaIndex, November 2022.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems LlamaIndex, November 2022

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.908507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 10ac8df4-d55f-48bc-96ba-7a765c799575 · outbound

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

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Query rewriting in retrieval- augmented large language models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.309472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d70fd096-6fe6-4f54-82b0-1fb4e3b91a22 · outbound

This paper cites an unresolved cited work.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:57:29.895245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0b0b4d00-a511-433a-8a51-7a80d0976a2d · outbound

This paper cites Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.317579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6d1309e-ad85-4dfe-a745-0b5d9877fbac · outbound

This paper cites REFINER: Reasoning feedback on in- termediate representations.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems REFINER: Reasoning feedback on in- termediate representations

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.881565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8f958e97-b7a1-4734-b9e6-903edb8d2ae9 · outbound

This paper cites Graph retrieval-augmented generation: A survey, 2024.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Graph retrieval-augmented generation: A survey, 2024

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.867207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d5c13841-28b1-49ef-b297-a0f6c1c2ad36 · outbound

This paper cites In-context retrieval-augmented language models.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems In-context retrieval-augmented language models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.852461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1baa4f23-5252-49d6-9b55-06a4acc277df · outbound

This paper cites Liu, and Bal- aji Lakshminarayanan.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Liu, and Bal- aji Lakshminarayanan

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.837196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 70c38100-54d6-4d6d-8fdf-cf3c7cbf75c5 · outbound

This paper cites an unresolved cited work.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Unresolved cited work

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.341882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58330162-95e3-4e5e-bb94-2b9d59ed899f · outbound

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

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.346056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28d1daf3-d268-4a21-bc91-86178f8e16f1 · outbound

This paper cites Le, Ed H.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Le, Ed H

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.823123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ca72815b-7e46-4982-86ab-9bd509dc7f5f · outbound

This paper cites Rossi, Alexa Siu, Ruiyi Zhang, and Tyler Derr.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Rossi, Alexa Siu, Ruiyi Zhang, and Tyler Derr

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.809225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dfe1e537-75a9-4199-810e-37116ff110e9 · outbound

This paper cites Chi, Quoc V.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Chi, Quoc V

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.795637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bec4b184-2be1-4b46-8a75-f6e54181971e · outbound

This paper cites Raft: Adapting language model to domain specific rag.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Raft: Adapting language model to domain specific rag

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:57:29.781604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 538cc9be-8990-4af5-a748-3c6718b5d4b9 · outbound

This paper cites Open-source large language mod- els are strong zero-shot query likelihood models for document ranking.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Open-source large language mod- els are strong zero-shot query likelihood models for document ranking

Reference 37

Resolution: verified exact; doi, observed 2026-08-07T04:57:29.415875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b760e46b-92dc-4700-b7ed-d2da798b1bdb · outbound

This paper cites Knowledge Graph Prompting for Multi-Document Question Answering.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems Knowledge Graph Prompting for Multi-Document Question Answering

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.359244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cea85eb9-3217-42a7-bac9-e309090d5b4a · outbound

This paper cites URL https: //aclanthology.org/2023.tacl-1.75.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems URL https: //aclanthology.org/2023.tacl-1.75

Reference 2023

Resolution: malformed identifier; no resolver link, observed 2026-08-07T04:57:29.333988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6707462c-6dae-4692-9939-23e184ab5269 · outbound

This paper cites ISBN 9798400704901.

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems ISBN 9798400704901

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.258534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d079ee60-ebf3-42be-9a27-16e453656a4b · outbound

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

FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T04:57:29.237268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 8d3150f6-d2ae-46d8-9818-bc62c3ab94fc · inbound

Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Directions for Building Trustworthy Systems cites this paper.

Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Directions for Building Trustworthy Systems FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-04T20:00:07.856153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 65cfce96-7ee9-4f28-b51b-74046f3586b4 · inbound

As We May Search cites this paper.

As We May Search FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T07:34:21.891583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.