Evaluating the factuality of long-form text generated by large language models (LMs) is non-
trivial because (1) generations often contain a mixture of supported and unsupported pieces …

Instruction-following models are attractive alternatives to fine-tuned approaches for question
answering (QA). By simply prepending relevant documents and an instruction to their input …

Recent years have witnessed remarkable progress made in large language models (LLMs).
Such advancements, while garnering significant attention, have concurrently elicited various …

Many individuals are likely to face a legal dispute at some point in their lives, but their lack of
understanding of how to navigate these complex issues often renders them vulnerable. The …

As language models are adopted by a more sophisticated and diverse set of users, the
importance of guaranteeing that they provide factually correct information supported by …

Nowadays, the quality of responses generated by different modern large language models
(LLMs) is hard to evaluate and compare automatically. Recent studies suggest and …

Existing works on long-term open-domain dialogues focus on evaluating model responses
within contexts spanning no more than five chat sessions. Despite advancements in long …

Foundation model development attracts a rapidly expanding body of contributors, scientists,
and applications. To help shape responsible development practices, we introduce the …

Abstract Retrieval-Augmented Generation (RAG) has recently emerged as a promising
solution to alleviate Large Language Model (LLM)'s deficiency in lack of knowledge. Existing …

Multimodal Vision Language Models (VLMs) have emerged as a transformative technology
at the intersection of computer vision and natural language processing, enabling machines …