2 citations · 3 across the 7 of their papers we have counts for
4 papers · 1 filter
Scaling Beyond Masked Diffusion Language Models
Subham Sekhar Sahoo, Jean-Marie Lemercier, Zhihan Yang +4
Diffusion language models are a promising alternative to autoregressive models due to their potential for faster generation. Among discrete diffusion approaches, Masked diffusion c…
FORESTLLM: Large Language Models Make Random Forest Great on Few-shot Tabular Learning
Zhihan Yang, Jiaqi Wei, Xiang Zhang +6
Tabular data high-stakes critical decision-making in domains such as finance, healthcare, and scientific discovery. Yet, learning effectively from tabular data in few-shot settings…
Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models
Marianne Arriola, Aaron Gokaslan, Justin T. Chiu +5
Diffusion language models offer unique benefits over autoregressive models due to their potential for parallelized generation and controllability, yet they lag in likelihood modeli…
Training Latent Variable Models with Auto-encoding Variational Bayes: A Tutorial
Yang Zhi-Han
Auto-encoding Variational Bayes (AEVB) is a powerful and general algorithm for fitting latent variable models (a promising direction for unsupervised learning), and is well-known f…