Huibin Wang — accepted AI-conference papers

2026

Automated Random Embedding for Practical Bayesian Optimization with Unknown Effective Dimension

Hong Qian, Xiang Shu, Xiang Xia, Xuhui Liu, Yangde Fu, Bei Liang +2

IJCAI 2026

Bayesian optimization is widely employed for optimizing complex black-box functions but struggles with the curse of dimensionality. Random embedding, as a dimension reduction strategy, simplifies tasks that possess the effective dimension by optimizing within a low-dimensional subspace. However, det

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2026

Next-ToBE: Probabilistic Next Token-Bag Exploitation for Activating Anticipatory Capacity in LLMs

Yihe Liu, Huibin Wang, Chenglin Wang, Jiahao Xiong, Pinyi Zhang, Xianming Hu +4

ICLR 2026poster

Auto-regressive large language models (LLMs) exhibit a non-trivial capacity to "anticipate'' long-range future tokens despite being trained to predict only one token at a time. Nevertheless, how to systematically profile, enhance and leverage such capacity to practically improve LLM reasoning perfor…

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