There is a resurgent interest in develo** intelligent open-domain dialog systems due to
the availability of large amounts of conversational data and the recent progress on neural …

Dialogue systems have achieved growing success in many areas thanks to the rapid
advances of machine learning techniques. In the quest for generating more human-like …

Most of the open-domain dialogue models tend to perform poorly in the setting of long-term
human-bot conversations. The possible reason is that they lack the capability of …

Maintaining consistent personas is essential for dialogue agents. Although tremendous
advancements have been brought, the limited-scale of annotated persona-dense data are …

While Reinforcement Learning from Human Feedback (RLHF) aligns Large Language
Models (LLMs) with general, aggregate human preferences, it is suboptimal for learning …

The advancements of neural dialogue generation models show promising results on
modeling short-text conversations. However, training such models usually needs a large …

Endowing dialogue systems with personas is essential to deliver more human-like
conversations. However, this problem is still far from well explored due to the difficulties of …

Zero-Shot Object Navigation (ZSON) enables agents to navigate towards open-vocabulary
objects in unknown environments. The existing works of ZSON mainly focus on following …

Introduction The growing demand for mental health support has highlighted the importance
of conversational agents as human supporters worldwide and in China. These agents could …

In recent years, Dialogue-style Large Language Models (LLMs) such as ChatGPT and GPT4
have demonstrated immense potential in constructing open-domain dialogue agents …