274 citations · 649 across the 21 of their papers we have counts for
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cs.CV2026
Loud and Clear: Making Visual Evidence Count in Multimodal Document RAG
Eunchan Jo, Seounghyun Jang, Sangwoo Mo
Multimodal document retrieval-augmented generation (RAG) has focused largely on retrieval, yet its answers depend on how well a vision-language model reads the retrieved pages. We…
cs.CV2026
Stay Fair! Ensuring Group Fairness in Diffusion Models Across Guidance Scales
Myeongsoo Kim, Eunji Kim, Minwoo Chae +1
Diffusion models steer conditional generation with a tunable guidance scale to trade off prompt alignment and diversity. However, existing debiasing techniques are optimized for a…