Cover Image

MultiRAG: A Knowledge-guided Framework for Mitigating Hallucination in Multi-source Retrieval Augmented Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Wenlong, Wang, Haofen, Li, Bohan, Huang, Peixuan, Zhao, Xinzhe, Liang, Lei
Format:	Preprint
Published:	2025
Subjects:	Information Retrieval Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

U-NIAH: Unified RAG and LLM Evaluation for Long Context Needle-In-A-Haystack
by: Gao, Yunfan, et al.
Published: (2025)

TagRAG: Tag-guided Hierarchical Knowledge Graph Retrieval-Augmented Generation
by: Tao, Wenbiao, et al.
Published: (2025)

Multi-Stage Verification-Centric Framework for Mitigating Hallucination in Multi-Modal RAG
by: Chen, Baiyu, et al.
Published: (2025)

MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation
by: Chang, Chia-Yuan, et al.
Published: (2024)

LexRAG: Benchmarking Retrieval-Augmented Generation in Multi-Turn Legal Consultation Conversation
by: Li, Haitao, et al.
Published: (2025)

DynaRAG: Bridging Static and Dynamic Knowledge in Retrieval-Augmented Generation
by: Liang, Penghao, et al.
Published: (2026)

HopRAG: Multi-Hop Reasoning for Logic-Aware Retrieval-Augmented Generation
by: Liu, Hao, et al.
Published: (2025)

Modular RAG: Transforming RAG Systems into LEGO-like Reconfigurable Frameworks
by: Gao, Yunfan, et al.
Published: (2024)

WeKnow-RAG: An Adaptive Approach for Retrieval-Augmented Generation Integrating Web Search and Knowledge Graphs
by: Xie, Weijian, et al.
Published: (2024)

LevelRAG: Enhancing Retrieval-Augmented Generation with Multi-hop Logic Planning over Rewriting Augmented Searchers
by: Zhang, Zhuocheng, et al.
Published: (2025)

FlexRAG: A Flexible and Comprehensive Framework for Retrieval-Augmented Generation
by: Zhang, Zhuocheng, et al.
Published: (2025)

S-Path-RAG: Semantic-Aware Shortest-Path Retrieval Augmented Generation for Multi-Hop Knowledge Graph Question Answering
by: Fu, Rong, et al.
Published: (2026)

FilterRAG: Zero-Shot Informed Retrieval-Augmented Generation to Mitigate Hallucinations in VQA
by: Sarwar, Nobin
Published: (2025)

Loops On Retrieval Augmented Generation (LoRAG)
by: Thakur, Ayush, et al.
Published: (2024)

TableRAG: A Retrieval Augmented Generation Framework for Heterogeneous Document Reasoning
by: Yu, Xiaohan, et al.
Published: (2025)

CIIR@LiveRAG 2025: Optimizing Multi-Agent Retrieval Augmented Generation through Self-Training
by: Salemi, Alireza, et al.
Published: (2025)

CORAL: Benchmarking Multi-turn Conversational Retrieval-Augmentation Generation
by: Cheng, Yiruo, et al.
Published: (2024)

Retrieval-Augmented Generation with Graphs (GraphRAG)
by: Han, Haoyu, et al.
Published: (2024)

FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research
by: Jin, Jiajie, et al.
Published: (2024)

IM-RAG: Multi-Round Retrieval-Augmented Generation Through Learning Inner Monologues
by: Yang, Diji, et al.
Published: (2024)

CausalRAG: Integrating Causal Graphs into Retrieval-Augmented Generation
by: Wang, Nengbo, et al.
Published: (2025)

Medico: Towards Hallucination Detection and Correction with Multi-source Evidence Fusion
by: Zhao, Xinping, et al.
Published: (2024)

Understanding Parametric Knowledge Injection in Retrieval-Augmented Generation
by: Tang, Minghao, et al.
Published: (2025)

ProRAG: Process-Supervised Reinforcement Learning for Retrieval-Augmented Generation
by: Wang, Zhao, et al.
Published: (2026)

Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study
by: Yu, Shuo, et al.
Published: (2024)

Toward Robust GraphRAG: Mitigating Retrieval Drift and Hallucination from Imperfect Knowledge Graphs
by: Ma, Yizhuo, et al.
Published: (2026)

MAO-ARAG: Multi-Agent Orchestration for Adaptive Retrieval-Augmented Generation
by: Chen, Yiqun, et al.
Published: (2025)

RAG-DIVE: A Dynamic Approach for Multi-Turn Dialogue Evaluation in Retrieval-Augmented Generation
by: Brehme, Lorenz, et al.
Published: (2026)

Chain-of-Retrieval Augmented Generation
by: Wang, Liang, et al.
Published: (2025)

GFM-RAG: Graph Foundation Model for Retrieval Augmented Generation
by: Luo, Linhao, et al.
Published: (2025)

Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering
by: Shi, Zhengliang, et al.
Published: (2024)

RAG-KG-IL: A Multi-Agent Hybrid Framework for Reducing Hallucinations and Enhancing LLM Reasoning through RAG and Incremental Knowledge Graph Learning Integration
by: Yu, Hong Qing, et al.
Published: (2025)

QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation
by: Min, Dehai, et al.
Published: (2025)

Generative Multi-Modal Knowledge Retrieval with Large Language Models
by: Long, Xinwei, et al.
Published: (2024)

Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning
by: Chen, Yiqun, et al.
Published: (2025)

HetaRAG: Hybrid Deep Retrieval-Augmented Generation across Heterogeneous Data Stores
by: Yan, Guohang, et al.
Published: (2025)

DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoning
by: Sun, Qingyun, et al.
Published: (2025)

Typed-RAG: Type-Aware Decomposition of Non-Factoid Questions for Retrieval-Augmented Generation
by: Lee, DongGeon, et al.
Published: (2025)

Research on the Online Update Method for Retrieval-Augmented Generation (RAG) Model with Incremental Learning
by: Fan, Yuxin, et al.
Published: (2025)

DomainRAG: A Chinese Benchmark for Evaluating Domain-specific Retrieval-Augmented Generation
by: Wang, Shuting, et al.
Published: (2024)