acceptodds: Which papers will get accepted at ICLR 2027?
Abstract
A prediction market on peer review. Each paper has a market on its decision (accept or reject), priced by researchers who stake $rep, an in app currency, on what they expect. Everyone who signs up receives 1,000 $rep to trade with. Prices are probabilities, and every market settles when the venue publishes its decisions. It is a game made for fun, and has no connection to ICLR, OpenReview or any other organisation. acceptodds is an open source project, open to contributions, at github.com/benedict-armstrong/acceptodds.1
- ETH Zurich
- University of Maryland, College Park
- University of Illinois Urbana-Champaign
- Birla Institute of Technology and Science, Pilani – Pilani Campus
- Pohang University of Science and Technology
- West Virginia University
- Amazon
- École Polytechnique Fédérale de Lausanne
- Harvard University
- Indian Institute of Technology Delhi
- Los Alamos National Laboratory
- Massachusetts Institute of Technology
- Mila
- Roche
- Technical University of Munich
- The Chinese University of Hong Kong
- University of California, Irvine
- University of Southern California
- University of Tübingen
- Virginia Tech
- 北京大学
- Aalto University
- Delhi Technological University
- ELLIS Institute Tübingen
- Emory University
- Indian Institute of Technology Kharagpur
- Industrial University of Santander
- INHA University
- Ludwig-Maximilians-Universität München
- Mohamed bin Zayed University of Artificial Intelligence
- National Taiwan University
- New York University
- Polytechnique Montréal
- Shanghai Jiao Tong University
- University of California, Los Angeles
- University of California, Santa Barbara
- University of Moratuwa
- University of Pennsylvania
- University of Surrey
- Uppsala University
[PDF]Correlation Structure Governs Scalarization Bias in a Group-Relative Reinforcement Learning System for Portfolio Optimization
[PDF]FASTER: Fast Adjoint Stochastic Transport for Endpoint Refinement in Reward-Guided Image Editing
[PDF]dVLA-RL: Reinforcement Learning over Denoising Trajectories for Discrete Diffusion Vision-Language-Action Models
[PDF]Why Fair Dataset Distillation Fails on Complex Distributions: A Geometric Analysis and a Spread-Preserving Remedy
1 If this project is interesting to you, reach out at [email protected].