1 citations · 1 across the 3 of their papers we have counts for
7 papers
HiPER: Hierarchical Reinforcement Learning with Explicit Credit Assignment for Large Language Model Agents
Jiangweizhi Peng, Yuanxin Liu, Ruida Zhou +4
Training LLMs as interactive agents for multi-turn decision-making remains challenging, particularly in long-horizon tasks with sparse and delayed rewards, where agents must execut…
Clinical Validation of Medical-based Large Language Model Chatbots on Ophthalmic Patient Queries with LLM-based Evaluation
Ting Fang Tan, Kabilan Elangovan, Andreas Pollreisz +13
Domain specific large language models are increasingly used to support patient education, triage, and clinical decision making in ophthalmology, making rigorous evaluation essentia…
Paying Less Generalization Tax: A Cross-Domain Generalization Study of RL Training for LLM Agents
Zhihan Liu, Lin Guan, Yixin Nie +6
Generalist LLM agents are often post-trained on a narrow set of environments but deployed across far broader, unseen domains. In this work, we investigate the challenge of agentic…
Local Linear Attention: An Optimal Interpolation of Linear and Softmax Attention For Test-Time Regression
Yifei Zuo, Yutong Yin, Zhichen Zeng +3
Transformer architectures have achieved remarkable success in various domains. While efficient alternatives to Softmax Attention have been widely studied, the search for more expre…
Advancing Object Goal Navigation Through LLM-enhanced Object Affinities Transfer
Mengying Lin, Shugao Liu, Dingxi Zhang +4
Object-goal navigation requires mobile robots to efficiently locate targets with visual and spatial information, yet existing methods struggle with generalization in unseen environ…
Just Say What You Want: Only-prompting Self-rewarding Online Preference Optimization
Ruijie Xu, Zhihan Liu, Yongfei Liu +4
We address the challenge of online Reinforcement Learning from Human Feedback (RLHF) with a focus on self-rewarding alignment methods. In online RLHF, obtaining feedback requires i…