3 papers
cs.CL2025
Training LLMs to be Better Text Embedders through Bidirectional Reconstruction
Chang Su, Dengliang Shi, Siyuan Huang +5
Large language models (LLMs) have increasingly been explored as powerful text embedders. Existing LLM-based text embedding approaches often leverage the embedding of the final toke…
cs.CV2025
X-MoGen: Unified Motion Generation across Humans and Animals
Xuan Wang, Kai Ruan, Liyang Qian +3
Text-driven motion generation has attracted increasing attention due to its broad applications in virtual reality, animation, and robotics. While existing methods typically model h…
cs.CV2024
BudgetFusion: Perceptually-Guided Adaptive Diffusion Models
Qinchan Li, Kenneth Chen, Changyue Su +1
Diffusion models have shown unprecedented success in the task of text-to-image generation. While these models are capable of generating high-quality and realistic images, the compl…