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cs.CV2026
From Token Correction to Claim Admission: Training-Free Hallucination Mitigation for Large Vision-Language Models
Hyeonggeun Han, Taehyun Cho, Sangwoo Hong
Large vision-language models often exhibit object hallucination, generating claims that are not supported by the input image. To mitigate this issue, we propose Evidence-Guided Vis…
cs.CV2025
Adjusting Initial Noise to Mitigate Memorization in Text-to-Image Diffusion Models
Hyeonggeun Han, Sehwan Kim, Hyungjun Joo +2
Despite their impressive generative capabilities, text-to-image diffusion models often memorize and replicate training data, prompting serious concerns over privacy and copyright.…
cs.CV2024
Mix from Failure: Confusion-Pairing Mixup for Long-Tailed Recognition
Youngseok Yoon, Sangwoo Hong, Hyungjun Joo +3
Long-tailed image recognition is a computer vision problem considering a real-world class distribution rather than an artificial uniform. Existing methods typically detour the prob…