6 citations · 16 across the 13 of their papers we have counts for
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cs.CV2025
VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models
Tianci Bi, Xiaoyi Zhang, Yan Lu +1
The performance of Latent Diffusion Models (LDMs) is critically dependent on the quality of their visual tokenizers. While recent works have explored incorporating Vision Foundatio…
cs.CL2025
TrInk: Ink Generation with Transformer Network
Zezhong Jin, Shubhang Desai, Xu Chen +8
In this paper, we propose TrInk, a Transformer-based model for ink generation, which effectively captures global dependencies. To better facilitate the alignment between the input…
cs.CL2025
LFD: Layer Fused Decoding to Exploit External Knowledge in Retrieval-Augmented Generation
Yang Sun, Zhiyong Xie, Lixin Zou +7
Retrieval-augmented generation (RAG) incorporates external knowledge into large language models (LLMs), improving their adaptability to downstream tasks and enabling information up…