4 papers
iCLP: Large Language Model Reasoning with Implicit Cognition Latent Planning
Sijia Chen, Di Niu
Large language models (LLMs), when guided by explicit textual plans, can perform reliable step-by-step reasoning during problem-solving. However, generating accurate and effective…
rSIM: Incentivizing Reasoning Capabilities of LLMs via Reinforced Strategy Injection
Sijia Chen, Baochun Li, Di Niu
Large language models (LLMs) are post-trained through reinforcement learning (RL) to evolve into Reasoning Language Models (RLMs), where the hallmark of this advanced reasoning is…
Calibre: Towards Fair and Accurate Personalized Federated Learning with Self-Supervised Learning
Sijia Chen, Ningxin Su, Baochun Li
In the context of personalized federated learning, existing approaches train a global model to extract transferable representations, based on which any client could train personali…
Toward Adaptive Reasoning in Large Language Models with Thought Rollback
Sijia Chen, Baochun Li
Large language models (LLMs) have been routinely used to solve various tasks using step-by-step reasoning. However, the structure of intermediate reasoning steps, or thoughts, is r…