Conversational information seeking (CIS) is concerned with a sequence of interactions
between one or more users and an information system. Interactions in CIS are primarily …

In this work, we introduce ChatQA, a suite of models that outperform GPT-4 on retrieval-
augmented generation (RAG) and conversational question answering (QA). To enhance …

Evaluation of Large Language Models (LLMs) is challenging because instruction-following
necessitates alignment with human values and the required set of skills varies depending on …

Large language models (LLMs) typically utilize the top-k contexts from a retriever in retrieval-
augmented generation (RAG). In this work, we propose a novel method called RankRAG …

Recent research on proactive conversational agents (PCAs) mainly focuses on improving
the system's capabilities in anticipating and planning action sequences to accomplish tasks …

Recent advancements in conversational systems have significantly enhanced human-
machine interactions across various domains. However, training these systems is …

Dialogue systems are designed to offer human users social support or functional services
through natural language interactions. Traditional conversation research has put significant …

As a cornerstone of modern information access, search engines have become
indispensable in everyday life. With the rapid advancements in AI and natural language …

Crosslingual conditional generation (eg, machine translation) has long enjoyed the benefits
of scaling. Nonetheless, there are still issues that scale alone may not overcome. A source …

The evolution of large language models (LLMs) has enhanced the planning capabilities of
language agents in diverse real-world scenarios. Despite these advancements, the potential …