Towards human-centered proactive conversational agents

Y Deng, L Liao, Z Zheng, GH Yang… - Proceedings of the 47th …, 2024 - dl.acm.org
Recent research on proactive conversational agents (PCAs) mainly focuses on improving
the system's capabilities in anticipating and planning action sequences to accomplish tasks …

Proactive Conversational AI: A Comprehensive Survey of Advancements and Opportunities

Y Deng, L Liao, W Lei, G Yang, W Lam… - ACM Transactions on …, 2025 - dl.acm.org
Dialogue systems are designed to offer human users social support or functional services
through natural language interactions. Traditional conversation research has put significant …

Affective computing in the era of large language models: A survey from the nlp perspective

Y Zhang, X Yang, X Xu, Z Gao, Y Huang, S Mu… - arxiv preprint arxiv …, 2024 - arxiv.org
Affective Computing (AC), integrating computer science, psychology, and cognitive science
knowledge, aims to enable machines to recognize, interpret, and simulate human emotions …

Mt-bench-101: A fine-grained benchmark for evaluating large language models in multi-turn dialogues

G Bai, J Liu, X Bu, Y He, J Liu, Z Zhou, Z Lin… - arxiv preprint arxiv …, 2024 - arxiv.org
The advent of Large Language Models (LLMs) has drastically enhanced dialogue systems.
However, comprehensively evaluating the dialogue abilities of LLMs remains a challenge …

Empowering large language models: Tool learning for real-world interaction

H Wang, Y Qin, Y Lin, JZ Pan, KF Wong - Proceedings of the 47th …, 2024 - dl.acm.org
Since the advent of large language models (LLMs), the field of tool learning has remained
very active in solving various tasks in practice, including but not limited to information …

Dialogbench: Evaluating llms as human-like dialogue systems

J Ou, J Lu, C Liu, Y Tang, F Zhang, D Zhang… - arxiv preprint arxiv …, 2023 - arxiv.org
Large language models (LLMs) have achieved remarkable breakthroughs in new dialogue
capabilities by leveraging instruction tuning, which refreshes human impressions of …

Can llms reason like humans? assessing theory of mind reasoning in llms for open-ended questions

M Amirizaniani, E Martin, M Sivachenko… - Proceedings of the 33rd …, 2024 - dl.acm.org
Theory of mind (ToM) reasoning involves understanding that others have intentions,
emotions, and thoughts, which is crucial for regulating one's reasoning. Although large …

Unims-rag: A unified multi-source retrieval-augmented generation for personalized dialogue systems

H Wang, W Huang, Y Deng, R Wang, Z Wang… - arxiv preprint arxiv …, 2024 - arxiv.org
Large Language Models (LLMs) has shown exceptional capabilities in many natual
language understanding and generation tasks. However, the personalization issue still …

TPE: Towards Better Compositional Reasoning over Cognitive Tools via Multi-persona Collaboration

H Wang, H Wang, L Wang, M Hu, R Wang… - … Conference on Natural …, 2024 - Springer
Previous works in tool learning mainly focus on the external function tools, such as models
and APIs, while overlooking the existence of cognitive tools inside the cognitive/thinking …

Conversational disease diagnosis via external planner-controlled large language models

Z Sun, C Luo, Z Liu, Z Huang - arxiv preprint arxiv:2404.04292, 2024 - arxiv.org
The development of large language models (LLMs) has brought unprecedented possibilities
for artificial intelligence (AI) based medical diagnosis. However, the application perspective …