Call for Paper

AI has made significant strides in various domains, including transformers, large language models, general AI, multi-modal representations, and generative models such as ChatGPT, Codex, HumAIns, and Adept. These advancements are poised to transform the field of digital assistants as they are becoming increasingly intelligent, autonomous, and better able to comprehend human work.

This workshop aims to unite researchers from different fields, such as programming languages, natural language processing, computer vision, knowledge representation, planning, human-computer interaction, and business process management. The primary objective is to establish a cross-disciplinary research agenda that will direct future work in the field of no-code digital apprentices and the AI-driven revolution in this area. By bringing together experts with diverse backgrounds, this workshop seeks to advance our understanding of the challenges and opportunities associated with NCDA and to encourage collaboration and innovation across disciplines.

We invite scientists, practitioners, and students from both academia and industry who share a passion for the potential ways in which AI can revolutionize the no-code automation field to participate in and submit their original work to this workshop. We encourage contributions that not only enhance NCDA with AI algorithms but also utilize their combination to address broader AI challenges. Moreover, we aim to attract individuals from research-oriented industrial divisions, such as Microsoft Research, Google Research, IBM Research, Adept.ai, and intelligence automation vendors like UiPath and Automation Anywhere. The workshop seeks to foster an open and collaborative atmosphere for exploring cutting-edge research and discussing innovative ideas in the field.

Submission Guidelines

Submissions must be written in English, prepared using the new CEUR-ART 1-column style, formatted in PDF and submitted via EasyChair.

An Overleaf template for LaTeX users is available here. Alternatively, you can download an offline version with the style files for both LaTeX and MS-Word.

Auto-Mates 2023 invites submissions of research, industry and application contributions as well as software demonstrations.

There are two paper submission formats:

• Regular papers up to 14 pages (excluding references): must contain enough substance that they can be cited in other publications and may not have appeared before.
• Extended Abstracts up to 4 pages (including references): results and ideas of interest to the Auto-Mates audience, including position papers, system and application descriptions and presentations of preliminary results, overview of papers accepted at another conference or which you submitted or plan to submit to another conference. In the latter case, extended abstracts must clearly state the venue where the paper has been accepted or submitted alongside its status.

Cool and exciting demos will be presented in a dedicated session at the workshop. Submissions are via email SUBMIT The submission must include a link to a video of the demo and a text description of both the demo and the core ideas. The submission deadline for the demos is June 2, 2023.

All accepted papers are expected to be presented at the conference and at least one author of each accepted paper must travel to the IJCAI venue in person. Multiple submissions of the same paper to other IJCAI workshops are forbidden.

Submissions should be single-blind so the names of the authors will be visible to the reviewers and should be indicated on the submitted files. In justified cases, if you wish your submission to be handled anonymously (i.e., double-blind) please send us an e-mail explaining the reasons. You will receive instructions on how to proceed.

List of Topics

• Teaching methods for no-code/low-code users
• AI for digital apprentices
• AI approaches for digital automation and robotic process automation
• Natural language processing for digital interaction and action transformers
• Multi-modal-based semantic representation of UI actions
• Multi-modal-based interfaces and human-computer interaction with digital apprentices
• Specification of tasks using prompts and dialogue
• End-user programming, validation, and supervision of AI-based automation systems
• Human-in-the-loop AI, human-AI collaboration, and human-centered AI
• Training and feedback approaches to support end-user customization of work
• Program generation and validation techniques, such as program synthesis
• Training and supervision methods
• AI as a teammate, and digital labor

Committees

Program Committee

• Jose Cambronero, Massachusetts Institute of Technology
• Eran Yahav, Technion
• Rotem Dror, University of Pennsylvania
• Xinyun Chen, Google
• Lior Limonad, IBM Research
• Nadia Polikarpova, University of California San Diego
• Sergey Zeltyn, IBM Research
• Rui Dong, University of Michigan
• Yan Chen, University of Toronto
• Yanju Chen, University of California, Santa Barbara
• Jiani Huang, University of Pennsylvania

Program Chairs

• Dr. Segev Shlomov
• Full Prof. Ronen Brafman
• Mr. Avi Yaeli
• Dr. Chenglong Wang
• Prof. Xinyu Wang

Publication

AutoMates@IJCAI23 proceedings will be published in CEUR-WS

Venue

The conference will be held in Macao S.A.R

Contact

All questions about submissions should be emailed to segev.shlomov1@ibm.com