Abstractive dialogue summarization is the task of distilling conversations into informative
and concise summaries. Although reviews have been conducted on this topic, there is a lack …

Meeting summarization has become a critical task considering the increase in online
interactions. While new techniques are introduced regularly, their evaluation uses metrics …

This paper evaluates the extent to which current Large Language Models (LLMs) can
capture task-oriented multi-party conversations (MPCs). We have recorded and transcribed …

We have deployed an LLM-based spoken dialogue system in a real hospital. The ARI social
robot embodies our system, which patients and their companions can have multi-party …

In this paper, we describe our setting and the architecture of our LLM-based dialogue
system embodied in a social robot and able to have multi-party conversations. Each …

Multi-party multi-turn dialogue comprehension brings unprecedented challenges in handling
complicated scenarios, as the co-occurrence of multiple speakers causes complexity and …

This paper investigates the pervasive issue of hate speech within Twitter/X Portuguese
network conversations, offering a multifaceted analysis of its characteristics. This study …

Advances in conversational AI systems, powered in particular by large language models,
have facilitated rapid progress in understanding and generating dialog. Typically, task …

Today's conversational robots largely lack multi-party abilities to differ-entiate between
human speakers, identify addressees of an utterance, understand complex social situations …

Tuning language models for dialogue generation has been a prevalent paradigm for
building capable dialogue agents. Yet, traditional tuning narrowly views dialogue generation …