10 papers
Salience Induction against Multi-Hop RAG Agents: Threat and Defense
Xingfu Zhou, Pengfei Wang, Yuan Zhou +2
Agentic retrieval-augmented generation (RAG) systems increasingly retrieve external evidence and orchestrate tools for knowledge-intensive applications. In Multi-Hop question answe…
Learn Before Represent: Bridging Generative and Contrastive Learning for Domain-Specific LLM Embeddings
Xiaoyu Liang, Yuchen Peng, Jiale Luo +3
Large Language Models (LLMs) adapted via contrastive learning excel in general representation learning but struggle in vertical domains like chemistry and law, primarily due to a l…
Reasoning-Style Poisoning of LLM Agents via Stealthy Style Transfer: Process-Level Attacks and Runtime Monitoring in RSV Space
Xingfu Zhou, Pengfei Wang
Large Language Model (LLM) agents relying on external retrieval are increasingly deployed in high-stakes environments. While existing adversarial attacks primarily focus on content…
AgentCTG: Harnessing Multi-Agent Collaboration for Fine-Grained Precise Control in Text Generation
Xinxu Zhou, Jiaqi Bai, Zhenqi Sun +2
Although significant progress has been made in many tasks within the field of Natural Language Processing (NLP), Controlled Text Generation (CTG) continues to face numerous challen…
FutureX: An Advanced Live Benchmark for LLM Agents in Future Prediction
Zhiyuan Zeng, Jiashuo Liu, Siyuan Chen +28
Future prediction is a complex task for LLM agents, requiring a high level of analytical thinking, information gathering, contextual understanding, and decision-making under uncert…
TreePO: Bridging the Gap of Policy Optimization and Efficacy and Inference Efficiency with Heuristic Tree-based Modeling
Yizhi Li, Qingshui Gu, Zhoufutu Wen +14
Recent advancements in aligning large language models via reinforcement learning have achieved remarkable gains in solving complex reasoning problems, but at the cost of expensive…