3 accepted papers
Evaluating large language model (LLM) is a complex task. Pairwise ranking has emerged as state-of-the-art method to evaluate human preferences by having humans compare pairs of LLM outputs based on predefined criteria, enabling ranking across multiple LLMs by aggregating pairwise results through alg…
Conventional approaches to text classification typically assume the existence of a fixed set of predefined labels to which a given text can be classified. However, in real-world applications, there exists an infinite label space for describing a given text. In addition, depending on the aspect (sent…
The increasing volume of commercially available conversational agents (CAs) on the market has resulted in users being burdened with learning and adopting multiple agents to accomplish their tasks. Though prior work has explored supporting a multitude of domains within the design of a single agent, t…