Paper Citation Record · LEDGER

Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2403.10446.

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

pith.paper-citation-record.v1
2403.10446 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 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 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:09:47.515290Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T22:29:09.351026Z

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 58f505df-1a39-49e2-9b5a-c20f99fb34a6 · inbound

Retrieval-Augmented Generation for AI-Generated Content: A Survey cites this paper.

Retrieval-Augmented Generation for AI-Generated Content: A Survey Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 158

Resolution: verified exact; arxiv_id, observed 2026-05-15T13:32:17.418401Z

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 c14993c3-47f1-4053-ba65-962ec5e4a8cf · inbound

Continually Self-Improving Language Models for Bariatric Surgery Question--Answering cites this paper.

Continually Self-Improving Language Models for Bariatric Surgery Question--Answering Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:47.515290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5fe19bc-d1fa-4af2-a6a9-eeaf5ac0688d · inbound

Novobo: Supporting Teachers' Peer Learning of Instructional Gestures by Teaching a Mentee AI-Agent Together cites this paper.

Novobo: Supporting Teachers' Peer Learning of Instructional Gestures by Teaching a Mentee AI-Agent Together Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T14:45:54.927732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb4e327f-98bd-4595-ace9-1a709e3e762c · inbound

MaskSearch: A Universal Pre-Training Framework to Enhance Agentic Search Capability cites this paper.

MaskSearch: A Universal Pre-Training Framework to Enhance Agentic Search Capability Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T13:59:16.493309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e83fc2ca-8db1-4bf8-955c-612320b1e65f · inbound

DRAGged into Conflicts: Detecting and Addressing Conflicting Sources in Search-Augmented LLMs cites this paper.

DRAGged into Conflicts: Detecting and Addressing Conflicting Sources in Search-Augmented LLMs Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T05:12:14.805959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a9f8471-bff2-4b7b-a1e3-cf9be5a7eeb9 · inbound

Reasoning RAG via System 1 or System 2: A Survey on Reasoning Agentic Retrieval-Augmented Generation for Industry Challenges cites this paper.

Reasoning RAG via System 1 or System 2: A Survey on Reasoning Agentic Retrieval-Augmented Generation for Industry Challenges Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T04:30:06.966462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee38a785-6be0-48a5-8820-74167ffe2ee1 · inbound

Fine-Tuning and Prompt Engineering of LLMs, for the Creation of Multi-Agent AI for Addressing Sustainable Protein Production Challenges cites this paper.

Fine-Tuning and Prompt Engineering of LLMs, for the Creation of Multi-Agent AI for Addressing Sustainable Protein Production Challenges Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T22:49:23.389504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31d7142f-67f4-4a27-bdbb-8ce83fe7b0a6 · inbound

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora cites this paper.

EraRAG: Efficient and Incremental Retrieval Augmented Generation for Growing Corpora Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T22:44:01.502044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c716b22d-b89b-4486-876d-e236ec55a949 · inbound

LLM-Assisted Question-Answering on Technical Documents Using Structured Data-Aware Retrieval Augmented Generation cites this paper.

LLM-Assisted Question-Answering on Technical Documents Using Structured Data-Aware Retrieval Augmented Generation Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T21:55:10.547533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ea10e22-f8c5-46b7-81c6-96588ea3f6b9 · inbound

A Survey on Proactive Defense Strategies Against Misinformation in Large Language Models cites this paper.

A Survey on Proactive Defense Strategies Against Misinformation in Large Language Models Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T20:03:47.476562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c30a6c78-9b49-49f0-82ce-a7691b3db6e4 · inbound

Context-Aware Search and Retrieval Over Erasure Channels cites this paper.

Context-Aware Search and Retrieval Over Erasure Channels Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T17:04:52.017343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a359d608-5344-4049-ac7d-a401460176e9 · inbound

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection cites this paper.

DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T15:48:57.081874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bc77e3e-3e6f-4f87-855d-734d562968a8 · inbound

From Sufficiency to Reflection: Reinforcement-Guided Thinking Quality in Retrieval-Augmented Reasoning for LLMs cites this paper.

From Sufficiency to Reflection: Reinforcement-Guided Thinking Quality in Retrieval-Augmented Reasoning for LLMs Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 9474

Resolution: unresolved; no resolver link, observed 2026-08-06T11:29:38.386764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf55aa04-a7ea-4db1-9a50-3554c3c6c819 · inbound

Integrating Rules and Semantics for LLM-Based C-to-Rust Translation cites this paper.

Integrating Rules and Semantics for LLM-Based C-to-Rust Translation Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-05T22:28:12.119271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7029a430-7d0d-40e0-8203-2c085df4a2dc · inbound

Quasiparticle interference in LiFeAs: Signature of inelastic tunneling through spin fluctuations cites this paper.

Quasiparticle interference in LiFeAs: Signature of inelastic tunneling through spin fluctuations Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T19:50:49.873196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7211c617-ecf1-48ee-a975-1b186f1a3c06 · inbound

Beyond Content Safety: Real-Time Monitoring for Reasoning Vulnerabilities in Large Language Models cites this paper.

Beyond Content Safety: Real-Time Monitoring for Reasoning Vulnerabilities in Large Language Models Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-15T00:48:24.967000Z

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 85b5f64b-aae1-40df-ad55-25819f10ef13 · inbound

Context-Aware Search and Retrieval Under Token Erasure cites this paper.

Context-Aware Search and Retrieval Under Token Erasure Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:31:03.909716Z

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 57112fdf-fc1e-45d0-b0fa-e990530dc1a1 · inbound

Development and Preliminary Evaluation of a Domain-Specific Large Language Model for Tuberculosis Care in South Africa cites this paper.

Development and Preliminary Evaluation of a Domain-Specific Large Language Model for Tuberculosis Care in South Africa Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T22:49:33.863166Z

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 5ad3cc0d-fefa-4990-9961-587d0b64d633 · inbound

HPC-LLM: Practical Domain Adaptation and Retrieval-Augmented Generation for HPC Support cites this paper.

HPC-LLM: Practical Domain Adaptation and Retrieval-Augmented Generation for HPC Support Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:29:09.353979Z

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 263d779e-ed64-4a94-ae31-5f52be93d2de · inbound

Towards FairRAG: Preventing Representational Harm in Retrieval-Augmented Generation by Enforcing Fair Exposure at Retrieval Time cites this paper.

Towards FairRAG: Preventing Representational Harm in Retrieval-Augmented Generation by Enforcing Fair Exposure at Retrieval Time Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:23:47.843523Z

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.