December 16th, 2023 
Daniela Lopez de Luise Dear all,
After numerous requests, we decided to push the deadline for the paper submission to October 8th, 2023. This is going to be the final submission date.
The workshop aims to bring together a diverse group of experts in the areas of neuroscience, machine learning, and reinforcement learning to discuss the strong potential of visual attention in various tasks spanning from data collection and annotation to causality, and medical imaging reading. Please find more information in the Call for Papers below.
Sincerely,
Dario Zanca on behalf of the organizing committee
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The 2023 Gaze Meets ML workshop in conjunction with NeurIPS 2023
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Webpage: https://gaze-meets-ml.github.io/
Twitter Handle: https://twitter.com/Gaze_Meets_ML
!!FINAL Submission deadline: October 8th, 2023!!
Location: New Orleans Convention Center, New Orleans, LA
** Overview **
We are excited to host the second edition of Gaze Meets ML workshop in December, 2023 in conjunction with NeurIPS 2023. The workshop will take place in-person at New Orleans! We’ve got a great lineup of speakers.
** Background **
Eye gaze has proven to be a cost-efficient way to collect large-scale physiological data that can reveal the underlying human attentional patterns in real life workflows, and thus has long been explored as a signal to directly measure human-related cognition in various domains Physiological data (including but not limited to eye gaze) offer new perception capabilities, which could be used in several ML domains, e.g., egocentric perception, embodiedAI, NLP, etc. They can help infer human perception, intentions, beliefs, goals and other cognition properties that are much needed for human-AI interactions and agent coordination. In addition, large collections of eye-tracking data have enabled data-driven modeling of human visual attention mechanisms, both for saliency or scanpath prediction, with twofold advantages: from the neuroscientific perspective to understand biological mechanisms better, from the AI perspective to equip agents with the ability to mimic or predict human behavior and improve interpretability and interactions.
With the emergence of immersive technologies, now more than any time there is a need for experts of various backgrounds (e.g., machine learning, vision, and neuroscience communities) to share expertise and contribute to a deeper understanding of the intricacies of cost-efficient human supervision signals (e.g., eye-gaze) and their utilization towards bridging human cognition and AI in machine learning research and development. The goal of this workshop is to bring together an active research community to collectively drive progress in defining and addressing core problems in gaze-assisted machine learning.
** Call for Papers **
We welcome submissions that present aspects of eye-gaze in regards to cognitive science, psychophysiology and computer science, propose methods on integrating eye gaze into machine learning, and application domains from radiology, AR/VR, autonomous driving, etc. that introduce methods and models utilizing eye gaze technology in their respective domains.
Topics of interest include but are not limited to the following:
- Understanding the neuroscience of eye-gaze and perception.
- State of the art in incorporating machine learning and eye-tracking.
- Annotation and ML supervision with eye-gaze.
- Attention mechanisms and their correlation with eye-gaze.
- Methods for gaze estimation and prediction using machine learning.
- Unsupervised ML using eye gaze information for feature importance/selection.
- Understanding human intention and goal inference.
- Using saccadic vision for ML applications.
- Use of gaze for human-AI interaction and agent coordination in multi-agent environments.
- Eye gaze used for AI, e.g., NLP, Computer Vision, RL, Explainable AI, Embodied AI, Trustworthy AI.
- Ethics of Eye Gaze in AI
- Gaze applications in cognitive psychology, radiology, neuroscience, AR/VR, autonomous cars, privacy, etc.
** Submission Guidelines **
The workshop will feature two tracks for submission: a full, archival proceedings track with accepted papers published in the Proceedings for Machine Learning Research (PMLR); and a non-archival, extended abstract track. Submissions to either track will undergo the same double-blind peer review. Full proceedings papers can be up to 15 pages and extended abstract papers can be up to 8 pages (both excluding references and appendices). Authors of accepted extended abstracts (non-archival submissions) retain full copyright of their work, and acceptance of such a submission to Gaze Meets ML does not preclude publication of the same material in another archival venue (e.g., journal or conference).
Please submit your paper at https://openreview.net/group?id=NeurIPS.cc/2023/Workshop/Gaze_Meets_ML
** Awards and Funding **
Possibly award prizes for best papers or cover registration fees of presenting authors with a focus on underrepresented minorities.
** Important dates for Workshop paper submission **
- Final paper submission deadline: October 8th, 2023
- Reviewing starts: September 30, 2023
- Reviewing ends: October 16, 2023
- Notification of acceptance: October 27, 2023
- Workshop: December 16 2023 (in person)
** Organizing Committee **
Amarachi Mbakwe (Virginia Tech)
Joy Wu (Stanford, IBM Research)
Dario Zanca (FAU Erlangen-Nürnberg)
Elizabeth Krupinski (Emory University)
Satyananda Kashyap (IBM Research)
Alex Karargyris (MLCommons)
** Contact **
Organizing Committee gaze.neurips@gmail.com
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Dario Zanca, Ph.D.
Machine Learning and Data Analytics Lab
Department Artificial Intelligence in Biomedical Engineering
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
Carl-Thiersch-Str. 2b, D-91052 Erlangen
Room 01.016
Phone number: +49 9131 85 20296 / +49 017686090120
Email: dario.zanca@fau.de
Website: https://www.mad.tf.fau.de/person/dario-zanca/
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