by Hsuan-Tien Lin, Ismini Lourentzou, Piotr Koniusz and Yarin Gal
We are excited to announce the list of NeurIPS 2023 workshops! We received 167 total submissions — a significant increase from last year. From this great batch of submissions, we have accepted 58 workshops that will take place in-person on Dec. 15 & 16.
We wish we could have accepted many more workshops given the exceptional quality of submissions this year, but technical and logistical constraints meant we could only accept a limited subset. This marks another year that workshop selection had to be selective, and we expect that many of the excellent proposals that we could not accept will be revised, resubmitted, and presented at other ML conferences.
Of course, we want to thank everyone who put in the effort to propose workshops. As Workshop Chairs, all we can do is guide the authors through the submission process. The actual work of organizing the workshops is done by the organizers. Thank you!
New This Year: Fully In-Person Workshops and Proposal Template
In contrast to the previous year, there will not be a separate virtual workshop day. All workshops are anticipated to be conducted in person. Our Call for Post-Conference Workshops emphasizes that NeurIPS will exclusively host in-person workshops this year, accompanied by comprehensive technical support to livestream the workshops to an online audience. We believe that this decision will offer the best experience for both the attendees present in person and those participating online. To assist proposal authors in preparing their proposals and enable reviewers to efficiently evaluate the key aspects of a successful workshop program, we introduced a proposal template this year. The template is experimental and its use is entirely optional for the proposal authors (although we strongly recommended its use). We are pleased to note that over 80% of the proposals adhered to or closely resembled the template. This greatly facilitated the organization and evaluation process, benefiting both proposal authors and reviewers alike.
Refinements: Review Process
We continued to use OpenReview as our submission platform this year, consistent with other NeurIPS submission tracks, due to the success of OpenReview in matching reviewers to proposals. We strived to ensure that every workshop proposal author had an OpenReview profile before the review period started, to better manage conflict-of-interests through OpenReview. Additional details about the selection process are provided below. Except for providing a proposal template, we did not alter requirements for the proposal much this year. We kept the length of the main proposal limited to three pages and the organizer information limited to two pages, along with unlimited references. We let reviewers know that they need not read beyond those pages.
Another point of feedback incorporated was to further refine the reviewing recruitment process. Thus, we increased the reviewer pool, with a focus on including more experienced organizers from past NeurIPS workshops as reviewers. As a result, we sent out over 300 invitations and managed to recruit 127 reviewers. This resulted in at least three reviews per proposal for all 167 proposals. The completion rate for assigned reviews reached 97%, and every proposal received at least three quality reviews. We thank all the reviewers for their timely and professional efforts to provide quality reviews that greatly assisted our decision-making and facilitated an exciting and well-informed workshop program this year.
In making our selections, we asked the reviewers to closely follow our Guidance for Workshop Proposals, which was also shared with the proposal authors. Workshop proposals must be reviewed somewhat differently from academic papers, and we therefore asked the reviewers to consider both scientific merits and broader impacts in their assessments. We recognize that workshop reviews might be somewhat more subjective than academic paper reviews. Following the practice of past years’ review process, we have decided not to release the reviews directly to the proposal authors. However, like last year, we released a short meta-review alongside the decision for each proposal — explaining how the proposal was perceived by the reviewers with the goal of highlighting what could be improved.
Individual evaluations of proposals by reviewers were important for the decision process, but they were not the only considerations in the decision process. For example, we also strived for a good balance between research areas, and between applications and theory. As interest across research areas is not uniform, some areas were more competitive than others. For example, as anticipated, there were many strong proposals surrounding large language models this year. We also received many submissions on important current topics such as privacy, fairness, and causality, as well as the connection between machine learning and other fields. We attempted to balance topics so they would cover both mainstays and emerging topics.
It is also worth noting that we saw many of the pitfalls in proposals also seen in previous years. This included leaning too heavily on past success of existing workshop series, unconfirmed or irrelevant speakers, insufficient time for discussion, scoping too big and too broad, and lip service to diversity.
The next step is for you to contribute! Several workshops have begun soliciting submissions, many using our suggested submission date of September 29, 2023. We typically let each workshop advertise its own call for papers (if they plan to include workshop papers). We will communicate with the workshop organizers some additional deadlines to facilitate the successful planning of 58 exciting workshops. Stay tuned for more technical and contextual information coming soon!
NeurIPS 2023 Accepted Workshops
On to the best part: the preliminary list of accepted workshops for 2023 (https://neurips.cc/virtual/2023/events/workshop):
- Backdoors in Deep Learning: The Good, the Bad, and the Ugly
- OPT 2023: Optimization for Machine Learning
- AI for Science: from Theory to Practice
- Generative AI for Education (GAIED): Advances, Opportunities, and Challenges
- Table Representation Learning Workshop
- NeurIPS 2023 Workshop on Machine Learning for Creativity and Design
- Temporal Graph Learning Workshop @ NeurIPS 2023
- NeurIPS 2023 Workshop on Tackling Climate Change with Machine Learning: Blending New and Existing Knowledge Systems
- NeurIPS 2023 Workshop on Generalization in Planning (GenPlan ’23)
- NeurIPS 2023 Workshop on AI for Accelerated Materials Design (AI4Mat-2023)
- Synthetic Data Generation with Generative AI
- NeurIPS 2023 Workshop on Diffusion Models
- The Symbiosis of Deep Learning and Differential Equations — III
- Gaze Meets ML
- Medical Imaging meets NeurIPS
- Information-Theoretic Principles in Cognitive Systems (InfoCog)
- Intrinsically Motivated Open-ended Learning (IMOL) Workshop
- Machine Learning with New Compute Paradigms
- Third Workshop on Efficient Natural Language and Speech Processing (ENLSP-III): The Future of Large Language & Speech Foundation Models
- Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS 2023 (FL@FM-NeurIPS’23)
- Heavy Tails in ML: Structure, Stability, Dynamics
- XAI in Action: Past, Present, and Future Applications
- AI meets Moral Philosophy and Moral Psychology: An Interdisciplinary Dialogue about Computational Ethics
- Agent Learning in Open-Endedness Workshop
- Socially Responsible Language Modelling Research (SoLaR)
- Foundation Models for Decision Making
- Associative Memory & Hopfield Networks in 2023
- Computational Sustainability: Promises and Pitfalls from Theory to Deployment
- MATH-AI: The 3rd Workshop on Mathematical Reasoning and AI
- Optimal Transport and Machine Learning
- Multi-Agent Security: Risks and Opportunities
- The NeurIPS 2023 Workshop on Goal-Conditioned Reinforcement Learning
- NeurIPS 2023 Workshop: Machine Learning and the Physical Sciences
- Workshop on robustness of zero/few-shot learning in foundation models (R0-FoMo)
- NeurIPS 2023 Workshop on Machine Learning for Audio
- Touch Processing: a new Sensing Modality for AI
- 4th Workshop on Self-Supervised Learning: Theory and Practice
- Machine Learning in Structural Biology Workshop
- Regulatable ML: Towards Bridging the Gaps between Machine Learning Research and Regulations
- 6th Robot Learning Workshop: Pretraining, Fine-Tuning, and Generalization with Large Scale Models
- NeurIPS 2023 Workshop on Learning-Based Solutions for Inverse Problems: Opportunities and Challenges
- Workshop on Distribution Shifts: New Frontiers with Foundation Models
- 6th Workshop on Artificial Intelligence for Humanitarian Assistance and Disaster Response
- Mathematics of Modern Machine Learning (M3L)
- I Can’t Believe It’s Not Better (ICBINB): Failure Modes in the Age of Foundation Models
- Generative AI for Biology
- New Frontiers of AI for Drug Discovery and Development
- Symmetry and Geometry in Neural Representations
- Algorithmic Fairness through the Lens of Time
- Machine Learning for Systems
- New Frontiers in Graph Learning (GLFrontiers)
- Adaptive Experimental Design and Active Learning in the Real World
- NeurIPS 2023 Workshop on Instruction Tuning and Instruction Following
- NeurIPS 2023 Workshop on Causal Representation Learning
- Attributing Model Behavior at Scale (ATTRIB)
- Deep Generative Models for Health
- UniReps: Unifying Representations in Neural Models
- Workshop on Advancing Neural Network Training: Computational Efficiency, Scalability, and Resource Optimization