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
- 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
- New York University
- Polytechnique Montréal
- University of California, Los Angeles
- University of California, Santa Barbara
- University of Moratuwa
- University of Pennsylvania
- University of Surrey
- Uppsala University
- Virginia Tech
- 北京大学
[PDF]SAGA: Spatially-Aware Gated Attention for Separating Outlier Structure from Functional Effect in Vision Transformers
[PDF]What Enables Motion Coordination in Talking Portrait Generation? From Cross-Domain Motion Representation to Alignment and Fusion
[PDF]CausalExoFormer: End-to-End Lag-Aware Causal Structure Learning for Exogenous Time-Series Forecasting
[PDF]Improving the Robustness of VLAs to Spatial Object Perturbation via Attention-Head Amplification
[PDF]FaceLinkGen: A Re-evaluation of Identity Leakage in Privacy-Preserving Face Recognition and Face Anonymization Systems Using Simple Distillation
1 If this project is interesting to you, reach out at [email protected].