Connectionists: Workshop on Attention - Deadline extended to Oct 3!

[Grace Lindsay]

The deadline to submit your attention-related papers has been extended to
**Oct 3**!

On behalf of the co-organizers, we would like to invite you to submit your
work to our NeurIPS workshop on “All things Attention: Bridging Different
Perspectives on Attention”. The details of the workshop and submission
instructions are as follows:


The Thirty Sixth Conference on Neural Information Processing Systems
(NeurIPS)

Dec 2, 2022

NeurIPS 2022 is a hybrid Conference

https://attention-learning-workshop.github.io/

The All Things Attention workshop aims to foster connections across
disparate academic communities that conceptualize "Attention" such as
Neuroscience, Psychology, Machine Learning, and Human-Computer Interaction.
Workshop topics of interest include (but are not limited to):


   1.

   Relationships between biological and artificial attention
   1.

      What are the connections between different forms of attention in the
      human brain and present deep neural network architectures?
      2.

      Can the anatomy of human attention models provide useful insights to
      researchers designing architectures for artificial systems?
      3.

      Given the same task and learning objective, do machines learn
      attention mechanisms that are different from humans?


   1.

   Attention for reinforcement learning and decision making
   1.

      How have reinforcement learning agents leveraged attention in
      decision making?
      2.

      Do decision-making agents today have implicit or explicit formalisms
      of attention?
      3.

      How can AI agents build notions of attention without explicitly baked
      in notions of attention?
      4.

      Can attention significantly enable AI agents to scale e.g. through
      gains in sample efficiency, and generalization?
      2.

   Benefits and formulation of attention mechanisms for continual /
   lifelong learning
   1.

      How can continual learning agents optimize for retention of knowledge
      for tasks that it already learned?
      2.

      How can the amount of interference between different inputs be
      controlled via attention?
      3.

      How does the executive control of attention evolve with learning in
      humans?
      4.

      How can we study the development of attentional systems in infancy
      and childhood to better understand how attention can be learned?
      3.

   Attention as a tool for interpretation and explanation
   1.

      How have researchers leveraged attention as a visualization tool?
      2.

      What are the common approaches when using attention as a tool for
      interpretability in AI?
      3.

      What are the major bottlenecks and common pitfalls in leveraging
      attention as a key tool for explaining the decisions of AI agents?
      4.

      How can we do better?
      4.

   The role of attention in human-computer interaction and human-robot
   interaction
   1.

      How do we detect aspects of human attention during interactions, from
      sensing to processing to representations?
      2.

      What systems benefit from human attention modeling, and how do they
      use these models?
      3.

      How can systems influence a user’s attention, and what systems
      benefit from this capability?
      4.

      How can a system communicate or simulate its own attention (humanlike
      or algorithmic) in an interaction, and to what benefit?
      5.

      How do attention models affect different applications, like
      collaboration or assistance, in different domains, like
autonomous vehicles
      and driver assistance systems, learning from demonstration,
joint attention
      in collaborative tasks, social interaction, etc.?
      6.

      How should researchers thinking about attention in different
      biological and computational fields organize the collection of human gaze
      data sets, modeling gaze behaviors, and utilizing gaze information in
      various applications for knowledge transfer and
cross-pollination of ideas?
      5.

   Attention mechanisms in Deep Neural Network (DNN) architectures
   1.

      How does attention in DNN such as transformers relate to existing
      formalisms of attention in cogsci/psychology?
      2.

      Do we have a concrete understanding of how and if self-attention in
      transformers contributes to its vast success in recent models
such as GPT2,
      GPT3, DALLE.?
      3.

      Can our understanding of attention from other fields inform the
      progress we have achieved in recent breakthroughs?


SUBMISSION INSTRUCTIONS

We invite you to submit papers (up to 9 pages for long papers and up to 5
pages for short papers, excluding references and appendix) in the NeurIPS
2022 format.
<https://neurips.cc/Conferences/2022/PaperInformation/StyleFiles> All
submissions will be managed through OpenReview (submission website
<https://openreview.net/group?id=NeurIPS.cc/2022/Workshop/Attention>). The
final submission including main paper, references and appendix should not
exceed 12 pages. Supplementary Materials uploads are to only be used
optionally for extra videos/code/data/figures and should be uploaded
separately in the submission website.

The review process is double-blind so the submission should be anonymized.
Accepted work will be presented as posters during the workshop, and select
contributions will be invited to give spotlight talks during the workshop.
Each accepted work entering the poster sessions will have an accompanying
pre-recorded 5-minute video. Please note that at least one coauthor of each
accepted paper will be expected to have a NeurIPS conference registration
and participate in one of the poster sessions.

Submissions will be evaluated based on novelty, rigor, and relevance to the
theme of the workshop. Both empirical and theoretical contributions are
welcome. Submissions should not have previously appeared in a journal or
conference (including accepted papers to NeurIPS 2022) and should not be
submitted to another NeurIPS workshop. Submissions must adhere to the
NeurIPS Code of Conduct.


The focus of the work should relate to the list of the topics specified
below. The review process will be double-blind and accepted submissions
will be presented as virtual talks or posters. There will be no proceedings
for this workshop, however, authors can opt to have their abstracts/papers
posted on the workshop website.

We encourage submissions on the following topics from the focus of bridging
different perspectives on attention:

   -

   Relationships between biological and artificial attention
   -

   Attention for reinforcement learning and decision making
   -

   Benefits and formulation of attention mechanisms for continual /
   lifelong learning
   -

   Attention as a tool for interpretation and explanation
   -

   The role of attention in human-computer interaction and human-robot
   interaction
   -

   Attention mechanisms in Deep Neural Network (DNN) architectures


Please submit your papers via the following link: submission website
<https://openreview.net/group?id=NeurIPS.cc/2022/Workshop/Attention>

IMPORTANT DATES

* Submission deadline: Oct 3 Sep 15, 2022 at 11:59PM (AOE) submission
website <https://openreview.net/group?id=NeurIPS.cc/2022/Workshop/Attention>


* Camera-ready (final) paper deadline: Nov 25, 2022 at 11:59PM (Anywhere on
earth)

* Workshop: Dec 2, 2022

CONFIRMED SPEAKERS & PANELISTS

Speakers:

Pieter Roelfsema (Netherlands Institute for Neuroscience)

James Whittington (University of Oxford)

Ida Momennejad (Microsoft Research)

Erin Grant (UC Berkeley)

Henny Admoni (Carnegie Mellon University)

Tobias Gerstenberg (Stanford University)

Vidhya Navalpakkam (Google Research)

Shalini De Mello (NVIDIA)

Panelists:

David Ha (Google Brain)

Pieter Roelfsema (Netherlands Institute for Neuroscience)

James Whittington (University of Oxford)

Ida Momennejad (Microsoft Research)

Henny Admoni (Carnegie Mellon University)

Tobias Gerstenberg (Stanford University)

Shalini De Mello (NVIDIA)

Ramakrishna Vedantam (Meta AI Research)

Megan deBettencourt (University of Chicago)

Cyril Zhang (Microsoft Research)


ORGANIZERS

Akanksha Saran (Microsoft Research, NYC)

Khimya Khetarpal (McGill University, Mila Montreal)

Reuben Aronson (Carnegie Mellon University)

Abhijat Biswas (Carnegie Mellon University)

Ruohan Zhang (Stanford University)

Grace Lindsay (University College London, New York University)

Scott Neikum (University of Texas at Austin, University of Massachusetts)


REGISTRATION

Participants should refer to the NeurIPS 2022 website (
https://neurips.cc/Conferences/2022/Dates) for information on how to
register.

CONTACT

Please reach out to us at attention-workshop at googlegroups.com  if you have
any questions. We look forward to receiving your submissions!


Kind Regards,

Workshop Organizers

All things Attention- Bridging different perspectives on attention
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