4 papers
Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based Optimizers
Andrew Zhao, Reshmi Ghosh, Vitor Carvalho +4
Large language model (LLM) systems increasingly power everyday AI applications such as chatbots, computer-use assistants, and autonomous robots, where performance often depends on…
Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?
Yang Yue, Zhiqi Chen, Rui Lu +4
Reinforcement Learning with Verifiable Rewards (RLVR) has recently demonstrated notable success in enhancing the reasoning performance of large language models (LLMs), particularly…
Towards Understanding Text Hallucination of Diffusion Models via Local Generation Bias
Rui Lu, Runzhe Wang, Kaifeng Lyu +3
Score-based diffusion models have achieved incredible performance in generating realistic images, audio, and video data. While these models produce high-quality samples with impres…
Towards Understanding the Benefit of Multitask Representation Learning in Decision Process
Rui Lu, Yang Yue, Andrew Zhao +2
Multitask Representation Learning (MRL) has emerged as a prevalent technique to improve sample efficiency in Reinforcement Learning (RL). Empirical studies have found that training…