Jiasheng Si

Large language models (LLMs) have demonstrated strong reasoning capabilities, and as existing approaches for enhancing LLM reasoning continue to mature, increasing attention has shifted toward meta-reasoning as a promising direction for further improvement. However, most existing meta-reasoning m...

With the generative capabilities of large language models (LLMs) reshaping the information ecosystem, the concern with the sociological validity of claim detection benchmarks is increasing. Current claim detection benchmarks predominantly treat claims as static textual artifacts, overlooking the...

Word sense disambiguation (WSD) is a foundational task in natural language processing. Recent research has reformulated WSD for large language models (LLMs) as a generative task, where the model produces a definition to convey the intended meaning of an ambiguous word in context.In practice, most...

Retrieval-Augmented Generation (RAG) mitigates hallucinations in large language models by incorporating external knowledge. However, retrieval does not always return relevant documents and may return noisy ones. Indiscriminately retrieving and utilizing this external knowledge can interfere with...