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stat.ML2026
Transformers as Cross-Task Learners: Shared Structure Drives Sample Efficiency in In-Context Learning
Zhongjie Shi, Rongjie Lai, Alexander Cloninger +1
Transformers achieve remarkable performance by jointly learning broad families of tasks during pretraining and adapting to unseen tasks from only a short prompt. Yet a rigorous mat…
stat.ML2026
Mode Coverage in Normalizing Flow Boltzmann Generators via Log-Ratio Variation
Qi Feng, Rongjie Lai, Di Qi +1
Normalizing flow Boltzmann generators retain a tractable pushforward density, but training with forward KL depends on target samples that may be biased or omit modes. As a result,…
stat.ML2025
Data-Driven Model Reduction using WeldNet: Windowed Encoders for Learning Dynamics
Biraj Dahal, Jiahui Cheng, Hao Liu +2
Many problems in science and engineering involve time-dependent, high dimensional datasets arising from complex physical processes, which are costly to simulate. In this work, we p…