This paper was accepted at the Fine-Tuning in Modern Machine Learning: Principles and Scalability (FITML) Workshop at NeurIPS 2024.
Large language models (LLMs) pretrained on large corpora of internet text possess much of the world's knowledge. Following pretraining, one...
Diffusion models have emerged as a powerful tool for generating high-quality images from textual descriptions. Despite their successes, these models often exhibit limited diversity in the sampled images, particularly when sampling with a high classifier-free guidance weight. To...
Multi-modal large language models (MLLMs) have enabled numerous advances in understanding and reasoning in domains like vision, but we have not yet seen this broad success for time-series. Although prior works on time-series MLLMs have shown promising performance...
