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While we do not always use words, communicating what we want to an AI is a conversation -- with ourselves as well as with it, a recurring loop with optional steps depending on the complexity of the situation and our request. Any given…

人机交互 · 计算机科学 2023-09-06 Elena L. Glassman

In our world with full of uncertainty, debates and argumentation contribute to the progress of science and society. Despite of the increasing attention to characterize human arguments, most progress made so far focus on the debate outcome,…

计算与语言 · 计算机科学 2020-02-11 Jichuan Zeng , Jing Li , Yulan He , Cuiyun Gao , Michael R. Lyu , Irwin King

The language generation and reasoning capabilities of large language models (LLMs) have enabled conversational systems with impressive performance in a variety of tasks, from code generation, to composing essays, to passing STEM and legal…

人工智能 · 计算机科学 2025-02-28 Konstantina Christakopoulou , Iris Qu , John Canny , Andrew Goodridge , Cj Adams , Minmin Chen , Maja Matarić

Winning competitive debates requires sophisticated reasoning and argument skills. There are unique challenges in the competitive debate: (1) The time constraints force debaters to make strategic choices about which points to pursue rather…

计算与语言 · 计算机科学 2025-12-22 Danqing Wang , Zhuorui Ye , Xinran Zhao , Fei Fang , Lei Li

In this paper, we present a deep reinforcement learning (RL) framework for iterative dialog policy optimization in end-to-end task-oriented dialog systems. Popular approaches in learning dialog policy with RL include letting a dialog agent…

计算与语言 · 计算机科学 2017-09-20 Bing Liu , Ian Lane

Though generative dialogue modeling is widely seen as a language modeling task, the task demands an agent to have a complex natural language understanding of its input text to carry a meaningful interaction with an user. The automatic…

计算与语言 · 计算机科学 2020-08-25 Prasanna Parthasarathi , Joelle Pineau , Sarath Chandar

Reaching consensus in urban planning is a complex process often hindered by prolonged negotiations, trade-offs, power dynamics, and competing stakeholder interests, resulting in inefficiencies and inequities. Advances in large language…

多智能体系统 · 计算机科学 2026-01-12 Jin Gao , Hanyong Xu , Luc Dao

The next step for intelligent dialog agents is to escape their role as silent bystanders and become proactive. Well-defined proactive behavior may improve human-machine cooperation, as the agent takes a more active role during interaction…

计算与语言 · 计算机科学 2023-06-23 Matthias Kraus , Nicolas Wagner , Ron Riekenbrauck , Wolfgang Minker

Growing literature explores toxicity and polarization in discourse, with comparatively less work on characterizing what makes dialogue prosocial and constructive. We explore conversational discourse and investigate a method for…

计算与语言 · 计算机科学 2025-11-04 Margaret Hughes , Brandon Roy , Elinor Poole-Dayan , Deb Roy , Jad Kabbara

As the interest in Artificial Intelligence continues to grow it is becoming more and more important to investigate formalization and tools that allow us to exploit logic to reason about the world. In particular, given the increasing number…

人工智能 · 计算机科学 2019-09-19 Francesco Fabiano

Conversational agents, also known as chatbots, are versatile tools that have the potential of being used in dialogical argumentation. They could possibly be deployed in tasks such as persuasion for behaviour change (e.g. persuading people…

人工智能 · 计算机科学 2019-05-03 Lisa A. Chalaguine , Anthony Hunter , Fiona L. Hamilton , Henry W. W. Potts

Writing persuasive arguments is a challenging task for both humans and machines. It entails incorporating high-level beliefs from various perspectives on the topic, along with deliberate reasoning and planning to construct a coherent…

计算与语言 · 计算机科学 2025-01-06 Zhe Hu , Hou Pong Chan , Jing Li , Yu Yin

Understanding the needs of a variety of distinct user groups is vital in designing effective, desirable dialogue systems that will be adopted by the largest possible segment of the population. Despite the increasing popularity of dialogue…

人机交互 · 计算机科学 2019-02-13 Libby Ferland , Thomas Huffstutler , Jacob Rice , Joan Zheng , Shi Ni , Maria Gini

Conversational grounding is a collaborative mechanism for establishing mutual knowledge among participants engaged in a dialogue. This experimental study analyzes information-seeking conversations to investigate the capabilities of large…

计算与语言 · 计算机科学 2024-06-05 Kristiina Jokinen , Phillip Schneider , Taiga Mori

Two ways has been discussed to unlock the reasoning capability of a large language model. The first one is prompt engineering and the second one is to combine the multiple inferences of large language models, or the multi-agent discussion.…

计算与语言 · 计算机科学 2023-11-14 Qineng Wang , Zihao Wang , Ying Su , Yangqiu Song

Different people have different habits of describing their intents in conversations. Some people tend to deliberate their intents in several successive utterances, i.e., they use several consistent messages for readability instead of a long…

计算与语言 · 计算机科学 2021-09-23 Zehao Lin , Shaobo Cui , Guodun Li , Xiaoming Kang , Feng Ji , Fenglin Li , Zhongzhou Zhao , Haiqing Chen , Yin Zhang

In open-domain conversational systems, it is important but challenging to leverage background knowledge. We can use the incorporation of knowledge to make the generation of dialogue controllable, and can generate more diverse sentences that…

人工智能 · 计算机科学 2021-05-06 Cheng Luo , Dayiheng Liu , Chanjuan Li , Li Lu , Jiancheng Lv

Opinion formation and persuasion in argumentation are affected by three major factors: the argument itself, the source of the argument, and the properties of the audience. Understanding the role of each and the interplay between them is…

计算与语言 · 计算机科学 2021-10-05 Esin Durmus

Conversational information access is an emerging research area. Currently, human evaluation is used for end-to-end system evaluation, which is both very time and resource intensive at scale, and thus becomes a bottleneck of progress. As an…

信息检索 · 计算机科学 2020-06-17 Shuo Zhang , Krisztian Balog

Methods for learning optimal policies in autonomous agents often assume that the way the domain is conceptualised---its possible states and actions and their causal structure---is known in advance and does not change during learning. This…

人工智能 · 计算机科学 2018-01-11 Craig Innes , Alex Lascarides , Stefano V Albrecht , Subramanian Ramamoorthy , Benjamin Rosman