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J. Foerster

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Preprint Oct 2026

Understanding the Inner Workings of a State-Space Foundation Model for Limit Order Books

Autoregressive foundation models offer state-of-the-art capabilities to simulate the market by generating the message flow of limit order books (LOBs). Yet, without understanding their inner workings, research directions are hard to narrow and practical use in real-world trading environments remains uncertain. This stu...

Valentin Mohl, Alexandre Bismuth, Aramis Marti-Shahandeh et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Q-Shaped Options for Hierarchical Reinforcement Learning

Q-Shaped Options (QSO) is introduced, which builds on an architecture with distinct state-value functions, Q functions and policies at each level of the hierarchy, and characterise three desiderata for an action abstraction.

C. Wibault, Antoine Gorceix, Antonio León Villares et al. · 0 citations
#machine learning Review Mar 2026

Measuring Progress in Reasoning Toward Mathematical Discovery with Automatic Verification

HorizonMath, a benchmark of 113 predominantly unsolved problems spanning eight domains in mathematics and the mathematical sciences, paired with an open-source evaluation framework for automated verification, is introduced, identifying six novel solutions to research problems that either resolve previously open questio...

Erik Y. Wang, S. Motwani, J. Roggeveen et al. · 6 citations
#artificial intelligence Preprint Sep 2026

CivBench: A Long-Horizon Benchmark for Tool-Mediated Agents in Civilization VI

CivBench is presented, an open-source benchmark for evaluating language model agents in long-horizon, tool-mediated environments through the Model Context Protocol (MCP), and two interface-level metrics are introduced that the environment makes measurable: Proactive Monitoring Rate (PMR) and RAG@10, capturing whether c...

Austin Andrews, L. Wilkinson, Jamie Heagerty et al. · 0 citations

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