3 papers
cs.LG2026
Efficient Reinforcement Learning for Large Language Models with Intrinsic Exploration
Yan Sun, Jia Guo, Stanley Kok +3
Reinforcement learning with verifiable rewards (RLVR) has improved the reasoning ability of large language models, yet training remains costly because many rollouts contribute litt…
cs.CL2026
Talk Less, Verify More: Improving LLM Assistants with Semantic Checks and Execution Feedback
Yan Sun, Ming Cai, Stanley Kok
As large language model (LLM) assistants become increasingly integrated into enterprise workflows, their ability to generate accurate, semantically aligned, and executable outputs…
cs.CL2025
Investigating the Effects of Cognitive Biases in Prompts on Large Language Model Outputs
Yan Sun, Stanley Kok
This paper investigates the influence of cognitive biases on Large Language Models (LLMs) outputs. Cognitive biases, such as confirmation and availability biases, can distort user…