Author

Yize Cheng

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Preprint Aug 2026

RAISE: Diagnosing Acquisition Collapse in Costly LLM Signals

Large language models (LLMs) are increasingly used as costly, on-demand components in real systems, but calling them indiscriminately can waste substantial compute, latency, and serving budget. The key deployment question is therefore not only whether an LLM helps on average, but when it is worth calling. We identify a...

Ying Yuan, Yu Wang, Yize Cheng et al. · 0 citations

#artificial intelligence Preprint Oct 2026

Hierarchical Reinforcement Learning with Stable Temporal Abstraction for Language Model Agents

Hierarchical reinforcement learning improves long-horizon control by organizing primitive actions around persistent subgoals and assigning credit at multiple temporal scales. Recent hierarchical language agents bring these benefits to interactive tasks by explicitly separating subgoal planning from action execution. We...

Shayan Mohajer Hamidi, Yize Cheng, Yuanda Xu et al. · 0 citations

Preprint Aug 2026

Thinking Hard, Not Smart: Reasoning Models Fail to Ration Test-Time Compute Across Questions

An exam-style evaluation framework is introduced for studying the global budget allocation of reasoning language models when multiple problems share an end-to-end cost or latency constraint, in which a model must distribute one shared token budget across questions with different difficulty and point values.

Chenrui Fan, Yize Cheng, Ming Li et al. · 0 citations