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
[PDF]Probabilistic Mixed-Effects Graph Autoencoding for Individualized Multi-Paradigm Functional Connectome Modeling
[PDF]RSI-Router: Cost-Efficient LLM Routing via Evolution of Subtask-Level Model Assignments with Execution Skills
[PDF]Prune Gradually, Adapt Sparsely: Efficient Pruning of Large Language Models at Extreme Sparsity
[PDF]SQ-Pruner: Spectral Saliency and Query-Guided Visual Token Pruning in Large Vision-Language Models
[PDF]Tokenize the Physics, Not the Pixels: TessTok and Fold-Flow Quantization for Material Microstructures
[PDF]When Better Prediction Makes Worse Generation: Teacher-Domain Alignment in Knowledge Distillation
[PDF]Task-Oriented Memory Compilation: Executable State Representations for Long-Context Language Models
[PDF]Beyond the Point Mass: Acceptance-Derived Weights and Distributional Losses for Speculative Decoding
[PDF]When Not to Trust a Global Gaussian Process Posterior: Local Scoring and Progressive Dissonance for Multi-Modal Scientific Discovery
[PDF]Large Distant Gradients Need Not Be Reliable: reliability-weighted credit assignment for long-horizon autoregressive forecasting
1 If this project is interesting to you, reach out at [email protected].