Bin Wu

Recent research empowers Large Language Models (LLMs) as multi-turn search agents to iteratively retrieve and generate outputs until complex tasks are solved. However, the contexts of multi-turn search agents are lengthy and complex. For example, the retrieved set of documents in each turn would...

Large language models (LLMs) increasingly act as tool-using agents , and existing methods for evaluating and optimizing tool usage by LLMs typically assume a static tool environment with fixed APIs and documentation. In practice, toolsets evolve as tools are added, changed, or deprecated, introdu...

Retrieval-Augmented Generation (RAG) is widely used for question answering over well-structured document corpora. However, a large amount of real-world problem-solving knowledge is captured in goal-oriented dialogues, where common ground misalignment between users and helpers gives rise to sparse...