Author

Chao Zhang

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#artificial intelligence Preprint Sep 2026

Forecast-Dojo: Replayable Environments for Benchmarking and Training LLM Forecasting Agents

Forecasting requires large language model (LLM) agents to gather evolving evidence, revise their beliefs, and make calibrated predictions over time. Yet evaluating and improving these capabilities is challenging because real-world events unfold continuously and outcomes may take months to resolve. We introduce Forecast...

Li-Qin Ye, Hao-Rui Wang, Fardin Ahmed et al. · 0 citations

Jul 2026

Matryoshka Agent: Unfolding Sub-Agents for Long-Horizon Machine Learning Engineering

Experimental results on a broad range of MLE tasks with diverse model types and scales demonstrate that Matryoshka Agent is an effective and scalable paradigm for long-horizon MLE tasks and complex agentic problem solving.

Rushi Qiang, Changhao Li, Haotian Sun et al. · arXiv.org · 0 citations