Yun Yue

Deep Incremental RNN for Learning Sequential Data: A Lyapunov Stable Dynamical System

2021

With the recent advances in mobile sensing technologies, large amounts of sequential data are collected, such as vehicle GPS records, stock prices, sensor data from air quality detectors. Recurrent neural networks (RNNs) have been studied …

Understanding Hyperbolic Metric Learning through Hard Negative Sampling

2024

In recent years, there has been a growing trend of incorporating hyperbolic geometry methods into computer vision. While these methods have achieved state-of-the-art performance on various metric learning tasks using hyperbolic distance measurements, the underlying …

Learning to Align, Aligning to Learn: A Unified Approach for Self-Optimized Alignment

2025 · arXiv (Cornell University)

Alignment methodologies have emerged as a critical pathway for enhancing language model alignment capabilities. While SFT (supervised fine-tuning) accelerates convergence through direct token-level loss intervention, its efficacy is constrained by offline policy trajectory. In contrast, …