Cover Image

Less is More: Denoising Knowledge Graphs For Retrieval Augmented Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zheng, Yilun, Yang, Dan, Li, Jie, Shang, Lin, Chen, Lihui, Xu, Jiahao, Luan, Sitao
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FanChuan: A Multilingual and Graph-Structured Benchmark For Parody Detection and Analysis
by: Zheng, Yilun, et al.
Published: (2025)

Say Less, Mean More: Leveraging Pragmatics in Retrieval-Augmented Generation
by: Riaz, Haris, et al.
Published: (2025)

What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks
by: Zheng, Yilun, et al.
Published: (2024)

Retrieval-Augmented Generation with Knowledge Graphs for Customer Service Question Answering
by: Xu, Zhentao, et al.
Published: (2024)

S$^2$DN: Learning to Denoise Unconvincing Knowledge for Inductive Knowledge Graph Completion
by: Ma, Tengfei, et al.
Published: (2024)

Personalizing Large Language Models using Retrieval Augmented Generation and Knowledge Graph
by: Prahlad, Deeksha, et al.
Published: (2025)

DrKGC: Dynamic Subgraph Retrieval-Augmented LLMs for Knowledge Graph Completion across General and Biomedical Domains
by: Xiao, Yongkang, et al.
Published: (2025)

Multiple Abstraction Level Retrieve Augment Generation
by: Zheng, Zheng, et al.
Published: (2025)

RAG in the Wild: On the (In)effectiveness of LLMs with Mixture-of-Knowledge Retrieval Augmentation
by: Xu, Ran, et al.
Published: (2025)

Retrieval-Augmented Generation Meets Data-Driven Tabula Rasa Approach for Temporal Knowledge Graph Forecasting
by: Sannidhi, Geethan, et al.
Published: (2024)

DH-RAG: A Dynamic Historical Context-Powered Retrieval-Augmented Generation Method for Multi-Turn Dialogue
by: Zhang, Feiyuan, et al.
Published: (2025)

Knowledge Graph-Guided Retrieval Augmented Generation
by: Zhu, Xiangrong, et al.
Published: (2025)

LIMR: Less is More for RL Scaling
by: Li, Xuefeng, et al.
Published: (2025)

Retrieval-Augmented Generation with Hierarchical Knowledge
by: Huang, Haoyu, et al.
Published: (2025)

Graph of Records: Boosting Retrieval Augmented Generation for Long-context Summarization with Graphs
by: Zhang, Haozhen, et al.
Published: (2024)

Less is More: Improving LLM Alignment via Preference Data Selection
by: Deng, Xun, et al.
Published: (2025)

Supernova: Achieving More with Less in Transformer Architectures
by: Tanase, Andrei-Valentin, et al.
Published: (2025)

Less Noise, More Voice: Reinforcement Learning for Reasoning via Instruction Purification
by: Guo, Yiju, et al.
Published: (2026)

Less is More: Local Intrinsic Dimensions of Contextual Language Models
by: Ruppik, Benjamin Matthias, et al.
Published: (2025)

A Survey on Knowledge-Oriented Retrieval-Augmented Generation
by: Cheng, Mingyue, et al.
Published: (2025)

Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts
by: Gan, Chunjing, et al.
Published: (2024)

A Graph-Retrieval-Augmented Generation Framework Enhances Decision-Making in the Circular Economy
by: Zhao, Yang, et al.
Published: (2025)

Less is More for Improving Automatic Evaluation of Factual Consistency
by: Wang, Tong, et al.
Published: (2024)

Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs
by: Wang, Junjie, et al.
Published: (2024)

LFD: Layer Fused Decoding to Exploit External Knowledge in Retrieval-Augmented Generation
by: Sun, Yang, et al.
Published: (2025)

A Few Words Can Distort Graphs: Knowledge Poisoning Attacks on Graph-based Retrieval-Augmented Generation of Large Language Models
by: Wen, Jiayi, et al.
Published: (2025)

A Pilot Empirical Study on When and How to Use Knowledge Graphs as Retrieval Augmented Generation
by: Yuan, Xujie, et al.
Published: (2025)

When More is Less: Understanding Chain-of-Thought Length in LLMs
by: Wu, Yuyang, et al.
Published: (2025)

Why Retrieval-Augmented Generation Fails: A Graph Perspective
by: Guo, Kai, et al.
Published: (2026)

RAVEN: In-Context Learning with Retrieval-Augmented Encoder-Decoder Language Models
by: Huang, Jie, et al.
Published: (2023)

Free(): Learning to Forget in Malloc-Only Reasoning Models
by: Zheng, Yilun, et al.
Published: (2026)

Explainable Lane Change Prediction for Near-Crash Scenarios Using Knowledge Graph Embeddings and Retrieval Augmented Generation
by: Manzour, M., et al.
Published: (2025)

DynaGRAG | Exploring the Topology of Information for Advancing Language Understanding and Generation in Graph Retrieval-Augmented Generation
by: Thakrar, Karishma
Published: (2024)

ControBench: An Interaction-Aware Benchmark for Controversial Discourse Analysis on Social Networks
by: Thuy, Ta Thanh, et al.
Published: (2026)

ReCellTy: Domain-Specific Knowledge Graph Retrieval-Augmented LLMs Reasoning Workflow for Single-Cell Annotation
by: Han, Dezheng, et al.
Published: (2025)

Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models
by: Wang, Fei, et al.
Published: (2024)

More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives
by: Zhang, Xiaoqing, et al.
Published: (2025)

Aggregated Knowledge Model: Enhancing Domain-Specific QA with Fine-Tuned and Retrieval-Augmented Generation Models
by: Liu, Fengchen, et al.
Published: (2024)

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation
by: Jiao, YiHan, et al.
Published: (2025)

Is Graph Convolution Always Beneficial For Every Feature?
by: Zheng, Yilun, et al.
Published: (2024)