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]Universal 2.030-Rounding for Multilayer Correlation Clustering with Probability Weights2 $rep15%
[PDF]Real-Time Causal Dynamics on Geometric Latent Spaces for Precision Therapeutic Monitoring37 $rep11%
[PDF]Exclusivity Without Marginal Loss: A Coupled-Rounding Primitive and Full-LP Obstruction for Chromatic Correlation Clustering2 $rep7%
[PDF]Aggregation Scale Shapes Anomaly-Duration Bias: Bounds, Readout Effects, and a Nonparametric Detector
[PDF]Efficient Online Estimation of Achievable Goal Distributions During Training for Goal-Conditioned Reinforcement Learning
[PDF]FunctionalMap: Learning Data-Driven Coordinates for Cross-Subject Transformer Modeling of Heterogeneous Intracranial Recordings
[PDF]Disclosure Begets Disclosure: A Self-Reinforcing Privacy Loop in LLM Agents with Persistent Memory
[PDF]Beyond Reverse Denoising: Efficiently Detecting Time Series Anomalies through Prototype-Guided Diffusion Inversion
[PDF]Hijacking the Instruction Hierarchy in LLM Agents: From Semantic Injection to Persistent Compromise
[PDF]BandSAD: Band-Decoupled Forecasting with Whitening for Label-Free Time-Series Anomaly Detection
[PDF]Do Jailbreaks Leave Identifiable Behavioral Footprints? Detection and Localization through Attention Occupancy
[PDF]Is Invariance All You Need For Algorithmic Fairness? Removing Demographic Information Can Create New Bias
1 If this project is interesting to you, reach out at [email protected].