6 papers · 1 filter
Topic-FlipRAG: Topic-Orientated Adversarial Opinion Manipulation Attacks to Retrieval-Augmented Generation Models
Yuyang Gong, Zhuo Chen, Jiawei Liu +5
Retrieval-Augmented Generation (RAG) systems based on Large Language Models (LLMs) have become essential for tasks such as question answering and content generation. However, their…
Every Part Matters: Integrity Verification of Scientific Figures Based on Multimodal Large Language Models
Xiang Shi, Jiawei Liu, Yinpeng Liu +2
This paper tackles a key issue in the interpretation of scientific figures: the fine-grained alignment of text and figures. It advances beyond prior research that primarily dealt w…
Black-Box Opinion Manipulation Attacks to Retrieval-Augmented Generation of Large Language Models
Zhuo Chen, Jiawei Liu, Haotan Liu +4
Retrieval-Augmented Generation (RAG) is applied to solve hallucination problems and real-time constraints of large language models, but it also induces vulnerabilities against retr…
Let's Learn Step by Step: Enhancing In-Context Learning Ability with Curriculum Learning
Yinpeng Liu, Jiawei Liu, Xiang Shi +3
Demonstration ordering, which is an important strategy for in-context learning (ICL), can significantly affects the performance of large language models (LLMs). However, most of th…
Enhance Robustness of Language Models Against Variation Attack through Graph Integration
Zi Xiong, Lizhi Qing, Yangyang Kang +5
The widespread use of pre-trained language models (PLMs) in natural language processing (NLP) has greatly improved performance outcomes. However, these models' vulnerability to adv…
From Model-centered to Human-Centered: Revision Distance as a Metric for Text Evaluation in LLMs-based Applications
Yongqiang Ma, Lizhi Qing, Jiawei Liu +5
Evaluating large language models (LLMs) is fundamental, particularly in the context of practical applications. Conventional evaluation methods, typically designed primarily for LLM…