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

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

Jiarui Li
Ye Yuan
Zehua Zhang
    RALM
ArXiv (abs)PDFHTML

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

4 / 4 papers shown
Title
Continually Self-Improving Language Models for Bariatric Surgery Question--Answering
Continually Self-Improving Language Models for Bariatric Surgery Question--Answering
Yash Kumar Atri
Thomas H Shin
Thomas Hartvigsen
45
1
0
22 May 2025
Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval
Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval
Pengcheng Jiang
Cao Xiao
Minhao Jiang
Parminder Bhatia
Taha A. Kass-Hout
Jimeng Sun
Jiawei Han
RALMAI4MH
168
7
0
06 Oct 2024
LinkQ: An LLM-Assisted Visual Interface for Knowledge Graph Question-Answering
LinkQ: An LLM-Assisted Visual Interface for Knowledge Graph Question-Answering
Harry Li
G. Appleby
Ashley Suh
77
2
0
07 Jun 2024
Discovering Latent Knowledge in Language Models Without Supervision
Discovering Latent Knowledge in Language Models Without Supervision
Collin Burns
Haotian Ye
Dan Klein
Jacob Steinhardt
140
383
0
07 Dec 2022

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.