6 papers
Two-Stage Score Estimation for Group-Specific Diffusion Models
Huitao Yang, Oscar Hernan Madrid Padilla
Generative modeling across related distributions raises a question: how can shared structure support accurate generation for a target distribution with limited observations? We dev…
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…
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…
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…
Greedy Selection under Independent Increments: A Toy Model Analysis
Huitao Yang
We study an iterative selection problem over N i.i.d. discrete-time stochastic processes with independent increments. At each stage, a fixed number of processes are retained based…
Fast Best-of-N Decoding via Speculative Rejection
Hanshi Sun, Momin Haider, Ruiqi Zhang +6
The safe and effective deployment of Large Language Models (LLMs) involves a critical step called alignment, which ensures that the model's responses are in accordance with human p…