Jiahai Wang

Large Language Models (LLMs) have emerged as powerful tools for passage reranking in information retrieval, leveraging their superior reasoning capabilities to address the limitations of conventional models on complex queries. However, current LLM-based reranking paradigms are fundamentally const...

Steering large language model (LLM) reasoning via high-level reasoning actions offers a promising approach to improve robustness and interpretability. However, existing action-based paradigms, ranging from training-free prompting to static plan retrieval or prediction, often fail to consistently...

Knowledge graph question answering (KGQA) serves as an essential benchmark for KG-enhanced large language models. Among various approaches, agent-based methods have emerged as an effective solution.Existing methods adopt entity-centric exploration that incrementally constructs reasoning paths by...