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cs.CV2026
UDT: Reconciling U-Nets and Diffusion Transformers with Data-Adaptive Token Reduction
Junno Yun, Yaşar Utku Alçalar, Mehmet Akçakaya
Diffusion Transformers (DiTs) have emerged as a core architecture in generative modeling due to their scalability and adaptability to multimodal tasks. DiTs comprise isotropic tran…
cs.CV2025
No Alignment Needed for Generation: Learning Linearly Separable Representations in Diffusion Models
Junno Yun, Yaşar Utku Alçalar, Mehmet Akçakaya
Efficient training strategies for large-scale diffusion models have recently emphasized the importance of improving discriminative feature representations in these models. A centra…