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cs.CL2025
Thinking Before You Speak: A Proactive Test-time Scaling Approach
Cong Liu, Wenchang Chai, Hejun Wu +3
Large Language Models (LLMs) often exhibit deficiencies with complex reasoning tasks, such as maths, which we attribute to the discrepancy between human reasoning patterns and thos…
cs.CV2025
Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions
ZiYi Dong, Chengxing Zhou, Weijian Deng +3
Contemporary diffusion models built upon U-Net or Diffusion Transformer (DiT) architectures have revolutionized image generation through transformer-based attention mechanisms. The…
cs.CV2025
Decoder-Only LLMs are Better Controllers for Diffusion Models
Ziyi Dong, Yao Xiao, Pengxu Wei +1
Groundbreaking advancements in text-to-image generation have recently been achieved with the emergence of diffusion models. These models exhibit a remarkable ability to generate hi…