Cover Image

RuleRAG: Rule-Guided Retrieval-Augmented Generation with Language Models for Question Answering

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Zhongwu, Xu, Chengjin, Wang, Dingmin, Huang, Zhen, Dou, Yong, Jiang, Xuhui, Guo, Jian
Format:	Preprint
Published:	2024
Subjects:	Information Retrieval Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Ruling Out to Rule In: Contrastive Hypothesis Retrieval for Medical Question Answering
by: Kim, Byeolhee, et al.
Published: (2026)

Arce: Augmented Roberta with Contextualized Elucidations for Ner in Automated Rule Checking
by: Chen, Jian, et al.
Published: (2025)

MUST-RAG: MUSical Text Question Answering with Retrieval Augmented Generation
by: Kwon, Daeyong, et al.
Published: (2025)

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

Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering
by: Siriwardhana, Shamane, et al.
Published: (2022)

Benchmarking Retrieval-Augmented Multimodal Generation for Document Question Answering
by: Dong, Kuicai, et al.
Published: (2025)

Preference-based Learning with Retrieval Augmented Generation for Conversational Question Answering
by: Kaiser, Magdalena, et al.
Published: (2025)

Decomposing Retrieval Failures in RAG for Long-Document Financial Question Answering
by: Kobeissi, Amine, et al.
Published: (2026)

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

SemRAG: Semantic Knowledge-Augmented RAG for Improved Question-Answering
by: Zhong, Kezhen, et al.
Published: (2025)

SQuAI: Scientific Question-Answering with Multi-Agent Retrieval-Augmented Generation
by: Besrour, Ines, et al.
Published: (2025)

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

KERAG: Knowledge-Enhanced Retrieval-Augmented Generation for Advanced Question Answering
by: Sun, Yushi, et al.
Published: (2025)

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

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

Pistis-RAG: Enhancing Retrieval-Augmented Generation with Human Feedback
by: Bai, Yu, et al.
Published: (2024)

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

Logic Rules as Explanations for Legal Case Retrieval
by: Sun, Zhongxiang, et al.
Published: (2024)

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

SRAG: Structured Retrieval-Augmented Generation for Multi-Entity Question Answering over Wikipedia Graph
by: Lin, Teng, et al.
Published: (2025)

Metacognitive Retrieval-Augmented Large Language Models
by: Zhou, Yujia, et al.
Published: (2024)

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

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

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

RAG-IGBench: Innovative Evaluation for RAG-based Interleaved Generation in Open-domain Question Answering
by: Zhang, Rongyang, et al.
Published: (2025)

Retrieval Augmented Generation for Domain-specific Question Answering
by: Sharma, Sanat, et al.
Published: (2024)

PAQA: Toward ProActive Open-Retrieval Question Answering
by: Erbacher, Pierre, et al.
Published: (2024)

MedCoT-RAG: Causal Chain-of-Thought RAG for Medical Question Answering
by: Wang, Ziyu, et al.
Published: (2025)

Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM Collaboration
by: Xu, Ran, et al.
Published: (2025)

Hierarchical Retrieval-Augmented Generation Model with Rethink for Multi-hop Question Answering
by: Zhang, Xiaoming, et al.
Published: (2024)

Comprehensive and Practical Evaluation of Retrieval-Augmented Generation Systems for Medical Question Answering
by: Ngo, Nghia Trung, et al.
Published: (2024)

ChatR1: Reinforcement Learning for Conversational Reasoning and Retrieval Augmented Question Answering
by: Lupart, Simon, et al.
Published: (2025)

REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering
by: Wang, Yuhao, et al.
Published: (2024)

M-RAG: Reinforcing Large Language Model Performance through Retrieval-Augmented Generation with Multiple Partitions
by: Wang, Zheng, et al.
Published: (2024)

RVR: Retrieve-Verify-Retrieve for Comprehensive Question Answering
by: Qian, Deniz, et al.
Published: (2026)

RAG-based Question Answering over Heterogeneous Data and Text
by: Christmann, Philipp, et al.
Published: (2024)

RAG based Question-Answering for Contextual Response Prediction System
by: Veturi, Sriram, et al.
Published: (2024)

SF-RAG: Structure-Fidelity Retrieval-Augmented Generation for Academic Question Answering
by: Yu, Rui, et al.
Published: (2026)

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

Optimizing Retrieval-Augmented Generation with Elasticsearch for Enhanced Question-Answering Systems
by: Chen, Jiajing, et al.
Published: (2024)