The emergence of tools based on large language models (LLMs), such as OpenAI's
ChatGPT and Google's Gemini, has garnered immense public attention owing to their …

Abstract The task of Question Answering (QA) has attracted significant research interest for a
long time. Its relevance to language understanding and knowledge retrieval tasks, along …

Despite efforts to expand the knowledge of large language models (LLMs), knowledge gaps-
-missing or outdated information in LLMs--might always persist given the evolving nature of …

While existing alignment paradigms have been integral in developing large language
models (LLMs), LLMs often learn an averaged human preference and struggle to model …

Explainable AI (XAI) refers to techniques that provide human-understandable insights into
the workings of AI models. Recently, the focus of XAI is being extended towards Large …

Large language models are limited by challenges in factuality and hallucinations to be
directly employed off-the-shelf for judging the veracity of news articles, where factual …

Role-playing has wide-ranging applications in customer support, embodied agents,
computational social science, etc. The influence of parametric world knowledge of large …

Retrieval augmented generation (RAG) combines the generative abilities of large language
models (LLMs) with external knowledge sources to provide more accurate and up-to-date …

Large language models (LLMs) augmented with external data have demonstrated
remarkable capabilities in completing real-world tasks. Techniques for integrating external …

We present Self-MoE, an approach that transforms a monolithic LLM into a compositional,
modular system of self-specialized experts, named MiXSE (MiXture of Self-specialized …