3 papers
cs.LG2025
Non-Markovian Discrete Diffusion with Causal Language Models
Yangtian Zhang, Sizhuang He, Daniel Levine +7
Discrete diffusion models offer a flexible, controllable approach to structured sequence generation, yet they still lag behind causal language models in expressive power. A key lim…
cs.LG2024
CaLMFlow: Volterra Flow Matching using Causal Language Models
Sizhuang He, Daniel Levine, Ivan Vrkic +6
We introduce CaLMFlow (Causal Language Models for Flow Matching), a novel framework that casts flow matching as a Volterra integral equation (VIE), leveraging the power of large la…
cs.LG2023
Operator Learning Meets Numerical Analysis: Improving Neural Networks through Iterative Methods
Emanuele Zappala, Daniel Levine, Sizhuang He +3
Deep neural networks, despite their success in numerous applications, often function without established theoretical foundations. In this paper, we bridge this gap by drawing paral…