to be held in conjunction with the
24th International Conference on Intelligent User Interfaces (ACM IUI 2019), 17-20 March 2019 in Los Angeles, USA.
https://iui.acm.org/2019/


Conversational agents are becoming increasingly used for various tasks, domains, and settings (e.g., personal assistants, customer service agents, intelligent tutors, and more), driven by recent advances in artificial intelligence and natural language processing. Conversational agent systems present an extremely rich and challenging research space for addressing many aspects of user awareness and adaptation, such as user profiles, contexts, personalities, emotions, social dynamics, conversational styles, etc. Adaptive interfaces are a long-standing interest for the HCI community, which has often made extensive efforts to study users, and prototype, evaluate, and design adaptive actions of computing systems.

Meanwhile, increasingly advanced machine learning approaches are introduced in new generations of conversational agents, such as deep learning, reinforcement learning, and active learning. It is imperative to consider how various aspects of user-awareness should be handled by these new techniques and system components for language understanding, language generation, dialog management, and in settings of end-to-end conversation modeling.

The goal of this workshop is to bring together researchers in HCI, user modeling, and the AI and NLP communities from both industry and academia, who are interested in advancing the state-of-the-art on the topic of user-aware conversational agents. Through a focused and open exchange of ideas and discussions, we will work to identify central research topics in user-aware conversational agents and develop a strong interdisciplinary foundation to address them.

IMPORTANT DATES
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Submission date Dec 7, 2018
Notifications send Jan 14, 2019
Camera-ready Feb 15, 2019
Workshop Date March 20, 2019


TOPICS OF INTEREST
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• User modeling for conversational agents and multi-modal interactions
• Sensing capabilities of agents (e.g., emotion, personality, contexts, social dynamic, etc.)
• Agent adaptation through language generation, dialog management and conversation modeling
• Personalization and adaptation algorithms inspired by behavioral or psychological theories
• Adapting agent interactions for user engagement
• Transparency and control of adaptive agents
• Novel methods for evaluating adaptive agents
• User interactions with and perceptions of adaptive agents
• Case studies of adaptive agents for different uses cases (e.g. collaborative tasks, decision support, social agent) and different domains (e.g. healthcare, finance, education)


SUBMISSION GUIDELINE
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IUI-user2agent encourages original and relevant work of two publication types:
• Full papers (up to 10 pages), including work in progress, perspective papers, and lessons learned. They will be presented either as oral presentations or posters.
• Position papers (up to 4 pages), which will be presented as posters with a possibility to be accompanied by a demo.

All papers should follow ACM SIGCHI templates: https://sigchi.org/templates/, and submitted electronically as a single PDF file through the EasyChair submission system: https://easychair.org/conferences/?conf=user2agent.

All submissions will undergo a peer-review process. Reviewers will consider originality, significance, technical soundness, clarity, and relevance to the workshop’s topics. The reviewing process will be double-blind.

Based on the results of the workshop, we plan to organize a special journal issue of the ACM Transactions on Interactive Intelligent Systems (TIIS) on this topic.

ORGANIZERS
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Yasaman Khazaeni, IBM Research AI, Cambridge Research Lab, USA
Q. Vera Liao, IBM Research AI, T.J. Watson Research Center, USA
Michal Shmueli-Scheuer, IBM Research AI, Haifa Research Lab, Israel
Tsung-Hsien (Shawn) Wen, PolyAI, UK
Zhou Yu, University of California, Davis, USA


Steering Committee
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Mari Ostendorf, University of Washington
Alex Rudnicky, CMU
Marilyn Walker, University of California, Santa Cruz
Michelle X. Zhou, Juji.io