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
- Industrial University of Santander
- Birla Institute of Technology and Science, Pilani – Pilani Campus
- University of California, Santa Barbara
- INHA University
- Polytechnique Montréal
- Aalto University
- Emory University
- Massachusetts Institute of Technology
- Uppsala University
- West Virginia University
- 北京大学
- Indian Institute of Technology Delhi
- The Chinese University of Hong Kong
- École Polytechnique Fédérale de Lausanne
- Los Alamos National Laboratory
- University of Maryland, College Park
- Harvard University
- Indian Institute of Technology Kharagpur
- New York University
- Mohamed bin Zayed University of Artificial Intelligence
- Indian Institute of Technology Dhanbad
- National Taiwan University
- Mila
- ETH Zurich
- University of Surrey
- Delhi Technological University
- Amazon
- University of California, Los Angeles
- Ludwig-Maximilians-Universität München
- Technical University of Munich
- University of Moratuwa
- University of Southern California
- Roche
- University of Illinois Urbana-Champaign
- University of Pennsylvania
- ELLIS Institute Tübingen
- University of Tübingen
- University of California, Irvine
- Virginia Tech
- Pohang University of Science and Technology
- Shanghai Jiao Tong University
[PDF]When Expressivity Does not Help: A Study of Linear and Nonlinear RNNs for Time Series Forecasting
[PDF]Guide the Tokens, Rank the Moments: Adaptive On-Policy Distillation for Temporal Video Grounding
[PDF]Quality Has a Direction: Learning a Shared Quality Axis from Reasoning for Image Quality Assessment
[PDF]Privacy-Preserving Deepfake Detection and Fine-Grained Artifact Localization with Forensic-Aware Image Hiding
[PDF]Interfaces and Modules: A Scalable Representation for Weight-Space Learning across Architectures
[PDF]VA-TDM: A Unified View for Improving Few-Step Diffusion Models by Velocity Adversarial Distillation
[PDF]Imbalance-aware NUMA Memory Placement: A Simple Approach To Mixture-of-Experts Serving on Tightly Coupled Architectures
[PDF]LIFT: Layout-In-Future Video Generation under Large Viewpoint Change via On-Policy Self-Distillation
[PDF]The Verifier-Bit Ledger: A Leakage Ceiling and an Executable Audit for Verifier-in-the-Loop Reasoning
[PDF]Topographic Soft Matching Distance (TSMD): A Framework for Comparing the Spatial Organization of Neural Tuning
1 If this project is interesting to you, reach out at [email protected].