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
- 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 Illinois Urbana-Champaign
- University of Tübingen
- Aalto University
- Delhi Technological University
- ELLIS Institute Tübingen
- Indian Institute of Technology Delhi
- Industrial University of Santander
- INHA University
- New York University
- University of California, Santa Barbara
- University of Pennsylvania
- University of Southern California
- University of Surrey
- Uppsala University
- Virginia Tech
- West Virginia University
[PDF]LeGramJEPA: Negative-Free Multimodal Graph Foundation Models in Latent Space with Volumetric Alignment and SIGReg
[PDF]FishNet 2.0: A Comprehensive Multimodal Benchmark for Long-Tailed Fine-Grained Fish Understanding
[PDF]Reconstruction Does Not Determine Generative Learnability: A Theory of Resource-Matched Visual Tokenization
[PDF]Faithful Is Not Forensic: Robust Intervention-based Forensic Testing (RIFT) for Auditing Deepfake Detectors
[PDF]Consensus-Breaking Re-rollout: Recovering Missing Action Contrasts for Long-Horizon Agent Reinforcement Learning
[PDF]WorldPortal: Recast Residual Correction for Instruction-Guided Video Background Replacement and Relighting
[PDF]ReAP: From Visual Failure Recognition to Action-Conditioned Risk Prediction for Runtime Failure Monitoring
[PDF]Video-OPD++: Geometry-Calibrated Corrective On-Policy Distillation for Temporal Video Grounding
[PDF]LoRA-Ring: Locality-Preserving Consistent Hashing for Dynamic Adapter Routing in Large Language Models
[PDF]Binding What to Where: Configurational Binding via On-Policy Self-Distillation for Multi-Object Spatial Reasoning
[PDF]Why MLLMs Struggle to Count: Overcoming Individuation and Aggregation Bottlenecks with ConvStack
[PDF]MAGE: Margin-Aligned Gradient Energy for Target-Supervised Robust Adaptation of Vision-Language Models
[PDF]Anchored but Not Protected: When Refusal Erodes During Fine-Tuning, and Whether Holding One Direction Stops It
[PDF]QUADS: Stabilizing NVFP4 Reinforcement Learning for MoE via QUantization-error Alignment across Dual Sides
1 If this project is interesting to you, reach out at [email protected].