Discussion and recommendations from the 2023 "Gaze Meets ML" workshop breakout session

Alexandros Karargyris, Shuaib Ahmed, Anthony Ryan de Belen, Bonny Banerjee, Timur Ibrayev, Satyananda Kashyap, Elizabeth Krupinski, Chenyi Kuang, Paul Madu, Amarachi Madu, Silvia Makowski, Athul Mathew, Tim Rolff, Bert Shi, Joy Wu, Danca Zario
Proceedings of The 2nd Gaze Meets ML workshop, PMLR 226:280-288, 2024.

Abstract

The Gaze Meets ML (GMML) workshop at NeurIPS aims to bring together diverse machine learning communities to foster research that leverages eye gaze (visual attention) to fulfill synergy between human attention/cognition and machine learning model development and evaluation. Towards this mission, the 2023 GMML workshop ran a breakout session to foster the research community by discussing open challenges. Three focus breakout session areas were identified through a selection process: Datasets, Community, and Vision and Actions for the Future. The findings and discussion points from this session were collected during the meeting and further organized and expanded after the meeting for efficient presentation here. The following sections detail each topic.

Cite this Paper

BibTeX
@InProceedings{pmlr-v226-karargyris24a, title = {Discussion and recommendations from the 2023 "Gaze Meets ML" workshop breakout session}, author = {Karargyris, Alexandros and Ahmed, Shuaib and de Belen, Ryan Anthony and Banerjee, Bonny and Ibrayev, Timur and Kashyap, Satyananda and Krupinski, Elizabeth and Kuang, Chenyi and Madu, Paul and Madu, Amarachi and Makowski, Silvia and Mathew, Athul and Rolff, Tim and Shi, Bert and Wu, Joy and Zario, Danca}, booktitle = {Proceedings of The 2nd Gaze Meets ML workshop}, pages = {280--288}, year = {2024}, editor = {Madu Blessing, Amarachi and Wu, Joy and Zario, Danca and Krupinski, Elizabeth and Kashyap, Satyananda and Karargyris, Alexandros}, volume = {226}, series = {Proceedings of Machine Learning Research}, month = {16 Dec}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v226/karargyris24a/karargyris24a.pdf}, url = {https://proceedings.mlr.press/v226/karargyris24a.html}, abstract = {The Gaze Meets ML (GMML) workshop at NeurIPS aims to bring together diverse machine learning communities to foster research that leverages eye gaze (visual attention) to fulfill synergy between human attention/cognition and machine learning model development and evaluation. Towards this mission, the 2023 GMML workshop ran a breakout session to foster the research community by discussing open challenges. Three focus breakout session areas were identified through a selection process: Datasets, Community, and Vision and Actions for the Future. The findings and discussion points from this session were collected during the meeting and further organized and expanded after the meeting for efficient presentation here. The following sections detail each topic.} }
Endnote
%0 Conference Paper %T Discussion and recommendations from the 2023 "Gaze Meets ML" workshop breakout session %A Alexandros Karargyris %A Shuaib Ahmed %A Anthony Ryan de Belen %A Bonny Banerjee %A Timur Ibrayev %A Satyananda Kashyap %A Elizabeth Krupinski %A Chenyi Kuang %A Paul Madu %A Amarachi Madu %A Silvia Makowski %A Athul Mathew %A Tim Rolff %A Bert Shi %A Joy Wu %A Danca Zario %B Proceedings of The 2nd Gaze Meets ML workshop %C Proceedings of Machine Learning Research %D 2024 %E Amarachi Madu Blessing %E Joy Wu %E Danca Zario %E Elizabeth Krupinski %E Satyananda Kashyap %E Alexandros Karargyris %F pmlr-v226-karargyris24a %I PMLR %P 280--288 %U https://proceedings.mlr.press/v226/karargyris24a.html %V 226 %X The Gaze Meets ML (GMML) workshop at NeurIPS aims to bring together diverse machine learning communities to foster research that leverages eye gaze (visual attention) to fulfill synergy between human attention/cognition and machine learning model development and evaluation. Towards this mission, the 2023 GMML workshop ran a breakout session to foster the research community by discussing open challenges. Three focus breakout session areas were identified through a selection process: Datasets, Community, and Vision and Actions for the Future. The findings and discussion points from this session were collected during the meeting and further organized and expanded after the meeting for efficient presentation here. The following sections detail each topic.
APA
Karargyris, A., Ahmed, S., de Belen, A.R., Banerjee, B., Ibrayev, T., Kashyap, S., Krupinski, E., Kuang, C., Madu, P., Madu, A., Makowski, S., Mathew, A., Rolff, T., Shi, B., Wu, J. & Zario, D.. (2024). Discussion and recommendations from the 2023 "Gaze Meets ML" workshop breakout session. Proceedings of The 2nd Gaze Meets ML workshop, in Proceedings of Machine Learning Research 226:280-288 Available from https://proceedings.mlr.press/v226/karargyris24a.html.

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