Knowledge Augmentation for Language Models

Follow this topic Ask about this topic

Momentum

11 papers in the last four weeks, up 120% on the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 111

All topics

How Large Language Models Balance Internal Knowledge with User and Document Assertions
Apr 24, 2026Shuowei Li, Haoxin Li, Wenda Chu +1LLM Sycophancy Knowledge Augmentation for Language Models
Santa Clara University · Nanyang Technological University · California Institute of Technology
BODHI: Precise OS Kernel Specification Inference
Apr 22, 2026Zhiming Chang, Ziyang LiKnowledge Augmentation for Language Models LLM Prompting
Department of Applied Mathematics and Statistics Johns Hopkins University Baltimore, US · Department of Computer Science Johns Hopkins University Baltimore, US
Effects of Cross-lingual Evidence in Multilingual Medical Question Answering
Apr 22, 2026Anar Yeginbergen, Maite Oronoz, Rodrigo AgerriKnowledge Augmentation for Language Models Healthcare
HiTZ Center - Ixa, University of the Basque Country UPV/EHU
Knowledge Capsules: Structured Nonparametric Memory Units for LLMs
Apr 22, 2026Bin Ju, Shenfeng Weng, Danying Zhou +2Memory-Augmented Language Models Knowledge Augmentation for Language Models
Zhejiang Angel Medical AI Technology Co., Ltd., Hangzhou, China · Miti AI Technology Co., Ltd., Hangzhou, China · China-Singapore Belt and Road Joint Laboratory on Translational Infection Biology for Diagnostics and Therapies, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital
Commonsense Knowledge with Negation: A Resource to Enhance Negation Understanding
Apr 21, 2026Zijie Wang, MohammadHossein Rezaei, Farzana Rashid +1Knowledge Augmentation for Language Models LLM Training
University of Arizona · University of North Carolina Asheville
Enhancing Mental Health Counseling Support in Bangladesh using Culturally-Grounded Knowledge
Apr 16, 2026Md Arid Hasan, Azhagu Meena SP, Aditya Khan +6Retrieval-Augmented Generation Mental Health Counseling
University of Toronto, Canada · mPower Social Enterprises Ltd, Bangladesh · National Institute of Mental Health, Bangladesh +2
Where Does Robustness Live? Neuron-Guided Adaptation for Retrieval-Augmented Language Models
Apr 2, 2026Jae O Lee, Jaemin Kim, Sumyeong Ahn +1Retrieval-Augmented Generation Fine-Tuning
1Hanyang University · 2KENTECH
Understanding LoRA as Knowledge Memory: An Empirical Analysis
Mar 1, 2026Seungju Back, Dongwoo Lee, Naun Kang +4Continual Learning for LLMs Memory-Augmented Language Models
1KAIST · 2Samsung SDS · 3New York University
Ontology-Guided Neuro-Symbolic Inference: Grounding Language Models with Mathematical Domain Knowledge
Feb 19, 2026Marcelo LabreRetrieval-Augmented Generation LLM Grounding
Advanced Institute for Artificial Intelligence (AI2)
SHINE: A Scalable In-Context Hypernetwork for Mapping Context to LoRA in a Single Pass
Feb 6, 2026Yewei Liu, Xiyuan Wang, Yansheng Mao +3Knowledge Augmentation for Language Models Low-Rank Adaptation
Institute for Artificial Intelligence, Peking University · School of Electronics Engineering and Computer Science, Peking University · University of Oxford +1
Edit Knowledge, Not Just Facts via Multi-Step Reasoning over Background Stories
Feb 2, 2026Ya Gao, Kalle Kujanpää, Pekka Marttinen +2Knowledge Editing Knowledge Augmentation for Language Models
Aalto University · System 2 AI
Predict the Retrieval! Test time adaptation for Retrieval Augmented Generation
Jan 16, 2026Xin Sun, Zhongqi Chen, Qiang Liu +5Retrieval-Augmented Generation Test-Time Adaptation
NLPR, MAIS, CASIA · Ant Group · USTC
RIMRULE: Improving Tool-Using Language Agents via MDL-Guided Rule Learning
Dec 31, 2025Xiang Gao, Yuguang Yao, Qi Zhang +5Knowledge Augmentation for Language Models LLM Tool Use
1Intuit AI Research · 2Temple University
AdaSearch: Balancing Parametric Knowledge and Search in Large Language Models via Reinforcement Learning
Dec 18, 2025Tzu-Han Lin, Wei-Lin Chen, Chen-An Li +3Retrieval-Augmented Generation Knowledge Augmentation for Language Models
National Taiwan University · Department of Computer Science, University of Virginia
Multilingual Medical Reasoning for Question Answering with Large Language Models
Dec 5, 2025Pietro Ferrazzi, Aitor Soroa, Rodrigo AgerriKnowledge Augmentation for Language Models Healthcare
Fondazione Bruno Kessler, Trento, Italy · HiTZ Center - Ixa, University of the Basque Country EHU, Spain
Zoom In Disparities in Healthcare LLM Q&A
Oct 20, 2025Ipek Baris Schlicht, Burcu Sayin, Zhixue Zhao +5Multilingual Language Model Evaluation Knowledge Augmentation for Language Models
Universitat Politècnica de València, Valencia, Spain · University of Trento, Trento, Italy · University of Sheffield, Sheffield, UK +5
Instruction Retrieval at Inference Time for Small Language Models
Oct 15, 2025Kenan Alkiek, David Jurgens, Vinod VydiswaranKnowledge Augmentation for Language Models Small Language Models
School of Information University of Michigan Ann Arbor, MI 48109, USA
Dataset Construction for Training LLM to Learn Analog Circuit Knowledge
Aug 14, 2025Zihao Chen, Ji Zhuang, Jinyi Shen +11Language Model Pretraining Knowledge Augmentation for Language Models
Fudan University, Shanghai, China
FlashBack: Efficient Retrieval-Augmented Language Modeling for Fast Inference
May 7, 2024Runheng Liu, Xingchen Xiao, Heyan Huang +2Knowledge Augmentation for Language Models LLM Inference Acceleration
School of Computer Science and Technology, Beijing Institute of Technology
All Entities are Not Created Equal: Examining the Long Tail for Ultra-Fine Entity Typing
Date pendingAdvait Deshmukh, Ashwin Umadi, Dananjay Srinivas +1Language Model Pretraining Long-Tail Learning
University of Colorado Boulder
MisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers
Date pendingZhihan Guo, Yuting Lu, Jionghao LinRetrieval-Augmented Generation Knowledge Augmentation for Language Models
The University of Hong Kong, Hong Kong SAR, China · Carnegie Mellon University, Pittsburgh PA 15213, USA · Monash University, Clayton VIC 3800, Australia

Apr 24, 2026, cs.CLJ/K move · Enter open · S save

How Large Language Models Balance Internal Knowledge with User and Document Assertions

Shuowei Li, Haoxin Li, Wenda Chu, Yi Fang

Santa Clara University · Nanyang Technological University · California Institute of Technology

LLM Sycophancy Knowledge Augmentation for Language Models Knowledge Conflicts in Language Models LLM Reliability LLM Safety

Open paper AskPDF arXiv

Large language models (LLMs) often need to balance their internal parametric knowledge with external information, such as user beliefs and content from retrieved documents, in real-world scenarios like RAG or chat-based systems. A model's ability to reliably process these sources is key to system safety. Previous studies on knowledge conflict and sycophancy are limited to a binary conflict paradigm, primarily exploring conflicts between parametric knowledge and either a document or a user, but ignoring the interactive environment where all three sources exist simultaneously. To fill this gap, we propose a three-source interaction framework and systematically evaluate 27 LLMs from 3 families on 2 datasets. Our findings reveal general patterns: most models rely more on document assertions than user assertions, and this preference is reinforced by post-training. Furthermore, our behavioral analysis shows that most models are impressionable, unable to effectively discriminate between helpful and harmful external information. To address this, we demonstrate that fine-tuning on diverse source interaction data can significantly increase a model's discrimination abilities. In short, our work paves the way for developing trustworthy LLMs that can effectively and reliably integrate multiple sources of information. Code is available at https://github.com/shuowl/llm-source-balancing.

Momentum

Related topics

Latest papers 111