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]How Does "English (US)” Become the Default? Triangulating Structural Bias Towards American English Across the LLM Pipeline100 $rep90%
[PDF]When Is One Reading Enough? Decision-Relevant Ambiguity in Constrained Reinforcement Learning200 $rep89%
[PDF]Back to the Roots? Rethinking Multilingual LLMs through Foundational Learner Vocabulary100 $rep88%
[PDF]CineSubBench: Evaluating LLMs on Long-Form Narrative and Cultural Understanding from Multilingual Movie Subtitles100 $rep88%
[PDF]Who Gets a Token, and What Does It Carry? Unequal Name Support and Concept Access in Large Language Models500 $rep86%
[PDF]SpectralEarth-FM: Bringing Hyperspectral Imagery into Multimodal Earth Observation Pretraining21 $rep86%
[PDF]ChronoSync: Recovering Long-Horizon Coupled Dynamics via Cross-Field Synchronization of Decoupled Diffusion Models22 $rep85%
[PDF]Spatial-as-Refinement: Gated Graph Operators over Strong Temporal Predictors for Scalable Spatio-Temporal Forecasting49 $rep84%
[PDF]The Floor That Barely Falls: Untrained Encoders as the Operative Null for Concept-Discovery Metrics220 $rep83%
[PDF]Early Warning of Personalization Model Degradation from User Histories and Hidden States199 $rep83%
[PDF]Leaderboards Display Ranks, Benchmarks Certify Tiers: Simultaneous Inference and a Capacity Law for LLM Evaluation49 $rep83%
[PDF]Bayesian Fine-tuning Yields Language Models that are as Bayesian as their Beliefs Allow100 $rep82%
[PDF]FlexLoop: Depth-Elastic Looped Policies for Adaptive Test-Time Computation in Deep RL42 $rep81%
[PDF]GMNO on MaxwellBench: Scaling Pretrained General Mesh Neural Operator Across Industrial-Standard Electromagnetism Simulations19 $rep81%
[PDF]PNEO: Pairwise Neural Energy Operators for Scalable Collision Dynamics of 3D Deformable Objects149 $rep81%
1 If this project is interesting to you, reach out at [email protected].