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
- Pohang University of Science and Technology
- Birla Institute of Technology and Science, Pilani – Pilani Campus
- University of Illinois Urbana-Champaign
- Amazon
- École Polytechnique Fédérale de Lausanne
- Harvard University
- Los Alamos National Laboratory
- Mila
- Roche
- Technical University of Munich
- The Chinese University of Hong Kong
- University of California, Irvine
- University of Tübingen
- West Virginia University
- Aalto University
- Delhi Technological University
- ELLIS Institute Tübingen
- Emory University
- Indian Institute of Technology Delhi
- Industrial University of Santander
- INHA University
- Massachusetts Institute of Technology
- New York University
- Polytechnique Montréal
- University of California, Santa Barbara
- University of Pennsylvania
- University of Southern California
- University of Surrey
- Uppsala University
- Virginia Tech
[PDF]Self-Configuring Hierarchies with Meta- Adaptive Hierarchical Reinforcement Learning for Multi-Agent Cooperative Control
[PDF]Characterizing Errors in Small Medical Language Models: Geometry, Prediction, and Causal Sensitivity
[PDF]FoldUMM: Unlocking Efficient Inference in Unified Multimodal Models via Task-Specific Layer Folding
[PDF]From Past Attempts to Better Decisions: Generalizing Verified Experience through Parametric Memory
[PDF]HiSTOR: Structured Treatment-outcome Representation Learning for High-Dimensional Longitudinal Data
[PDF]PhysDEM: Physics-Defined Energy-Matching Diffusion for Spatiotemporal Field Generation under Scarce Measurements
[PDF]CLOVER: Coverage-Led Optimization of Verifiable Evidence Reasoning for AI-Generated Image Detection
[PDF]H-MSAE: Hierarchical Sparse Concept Coverage for Efficient and Diverse Instruction Data Selection
[PDF]The Selection Rule Decides the Winner: A Pre-Registered Audit of Open-Set Graph Anomaly Detection
1 If this project is interesting to you, reach out at [email protected].