4 papers
EUBRL: Epistemic Uncertainty Directed Bayesian Reinforcement Learning
Jianfei Ma, Wee Sun Lee
At the boundary between the known and the unknown, an agent inevitably confronts the dilemma of whether to explore or to exploit. Epistemic uncertainty reflects such boundaries, re…
Beyond Imitation: Reinforcement Learning for Active Latent Planning
Zhi Zheng, Wee Sun Lee
Aiming at efficient and dense chain-of-thought (CoT) reasoning, latent reasoning methods fine-tune Large Language Models (LLMs) to substitute discrete language tokens with continuo…
SofT-GRPO: Surpassing Discrete-Token LLM Reinforcement Learning via Gumbel-Reparameterized Soft-Thinking Policy Optimization
Zhi Zheng, Yu Gu, Wei Liu +2
The soft-thinking paradigm for Large Language Model (LLM) reasoning can outperform the conventional discrete-token Chain-of-Thought (CoT) reasoning in some scenarios, underscoring…
Reasoning-CV: Fine-tuning Powerful Reasoning LLMs for Knowledge-Assisted Claim Verification
Zhi Zheng, Wee Sun Lee
Claim verification is essential in combating misinformation, and large language models (LLMs) have recently emerged in this area as powerful tools for assessing the veracity of cla…