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cs.LG2026
Learning to Extrapolate in Depth with Looped Transformers
Huitao Yang, Jianhao Huang, Zixuan Wang +1
Looped transformers reuse a single block across iterations, raising a natural question: how far can a block trained at one depth be safely extrapolated to greater depths? We study…
cs.LG2026
Let the Target Select for Itself: Data Selection via Target-Aligned Paths
Huitao Yang, Hengzhi He, Guang Cheng +1
Targeted data selection seeks training examples from a candidate pool that improve downstream task performance. While trajectory-based selectors effectively guide this process, exi…
cs.LG2025
In-Context Curiosity: Distilling Exploration for Decision-Pretrained Transformers on Bandit Tasks
Huitao Yang, Guanting Chen
As large language models (LLMs) continue to grow in capability, there is increasing interest in incorporating them into decision-making tasks. A common pipeline for this is Decisio…