Dutch Books for Language Models

arXiv:2609.02797 · econ.GN, cs.AI, cs.CL, cs.LG, q-fin.EC · Submitted 2026-09-02 · Read on arXiv

econ.GN, cs.AI, cs.CL, cs.LG, q-fin.EC

Submitted: 2026-09-02

Updated: 2026-09-02

Terminology

• Accuracy — 8× in this paper · explained in 1 episode
• Consistency — 6× in this paper · explained in 3 episodes
• Calibration — 5× in this paper · explained in 7 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• World Model — 4× in this paper · explained in 7 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Mode Collapse — 1× in this paper · explained in 2 episodes
• Probabilistic Forecasting — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Self-consistency — 1× in this paper · explained in 2 episodes

Sources

• AIA Forecaster: Technical Report
• Revealed Rationality: Label-Free Evaluation and Regularization from Representation Theorems
• PolyBench: Benchmarking LLM Forecasting and Trading Capabilities on Live Prediction Market Data
• Language Models (Mostly) Know What They Know
• Elicitation Matters: How Prompts and Query Protocols Shape LLM Surrogates under Sparse Observations
• Do Large Language Models Know What They Don't Know? Kalshibench: A New Benchmark for Evaluating Epistemic Calibration via Prediction Markets
• Poly-EPO: Training Exploratory Reasoning Models

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