4 papers
Multi-LLM Collaborative Search for Complex Problem Solving
Sen Yang, Yafu Li, Wai Lam +1
Large language models (LLMs) often struggle with complex reasoning tasks due to their limitations in addressing the vast reasoning space and inherent ambiguities of natural languag…
Not All Preference Pairs Are Created Equal: A Recipe for Annotation-Efficient Iterative Preference Learning
Sen Yang, Leyang Cui, Deng Cai +3
Iterative preference learning, though yielding superior performances, requires online annotated preference labels. In this work, we study strategies to select worth-annotating resp…
Neuro-Symbolic Integration Brings Causal and Reliable Reasoning Proofs
Sen Yang, Xin Li, Leyang Cui +2
Two lines of approaches are adopted for complex reasoning with LLMs. One line of work prompts LLMs with various reasoning structures, while the structural outputs can be naturally…
Once Upon a in : Relative-Time Pretraining for Complex Temporal Reasoning
Sen Yang, Xin Li, Lidong Bing +1
Our physical world is constantly evolving over time, rendering challenges for pre-trained language models to understand and reason over the temporal contexts of texts. Existing wor…