5 papers
Nexus: Same Pretraining Loss, Better Downstream Generalization via Common Minima
Huanran Chen, Huaqing Zhang, Xiao Li +3
The foundational capabilities of large language models are acquired during pretraining on internet-scale, highly heterogeneous data mixtures. In this work, we investigate an intere…
A Closer Look on Memorization in Tabular Diffusion Model: A Data-Centric Perspective
Zhengyu Fang, Zhimeng Jiang, Huiyuan Chen +4
Diffusion models have shown strong performance in generating high-quality tabular data, but they carry privacy risks by reproducing exact training samples. While prior work focuses…
Dataset-Level Metrics Attenuate Non-Determinism: A Fine-Grained Non-Determinism Evaluation in Diffusion Language Models
Zhengyu Fang, Zhimeng Jiang, Huiyuan Chen +5
Diffusion language models (DLMs) have emerged as a promising paradigm for large language models (LLMs), yet the non-deterministic behavior of DLMs remains poorly understood. The ex…
Understanding and Mitigating Memorization in Diffusion Models for Tabular Data
Zhengyu Fang, Zhimeng Jiang, Huiyuan Chen +2
Tabular data generation has attracted significant research interest in recent years, with the tabular diffusion models greatly improving the quality of synthetic data. However, whi…
Recent Developments in GNNs for Drug Discovery
Zhengyu Fang, Xiaoge Zhang, Anyin Zhao +3
In this paper, we review recent developments and the role of Graph Neural Networks (GNNs) in computational drug discovery, including molecule generation, molecular property predict…