Author

Ruijie Wang

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Preprint Aug 2026

Counterfactual Quotient Models: Learning What Actions Change, Not What the World Does

This work introduces the Counterfactual Quotient Model, which treats action-conditioned futures as equivalent when they differ only by a component shared across actions, and establishes the decision sufficiency, identifiability, common-mode invariance, approximation behavior, and regret properties of the resulting representation.

Junlin Chen, Ruijie Wang, Jianxin Li · 0 citations

#artificial intelligence Preprint Aug 2026

LLMODE: Aligning ODEs with LLMs via Gated Token Injection for Irregular Spatio-Temporal Forecasting

LLMODE is proposed, a token-efficient framework for irregular spatio-temporal forecasting with a frozen LLM backbone that shows competitive overall performance, with clearer advantages under sparse or dynamically complex irregular sampling.

Di Zhang, Jing-Yang Zhang, Zi-Qian Wang et al. · 0 citations