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From the 1 of 15 linked papers with an AI index.

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20242026
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cs.CV2026

RL makes MLLMs see better than SFT

Junha Song, Sangdoo Yun, Dongyoon Han +2

A dominant assumption in Multimodal Language Model (MLLM) research is that its performance is largely inherited from the LLM backbone, given its immense parameter scale and remarka…

cs.CV2026

Exploring Conditions for Diffusion models in Robotic Control

Heeseong Shin, Byeongho Heo, Dongyoon Han +2

While pre-trained visual representations have significantly advanced imitation learning, they are often task-agnostic as they remain frozen during policy learning. In this work, we…

cs.CV2026

Token Bottleneck: One Token to Remember Dynamics

Taekyung Kim, Dongyoon Han, Byeongho Heo +2

Deriving compact and temporally aware visual representations from dynamic scenes is essential for successful execution of sequential scene understanding tasks such as visual tracki…

cs.CV2025

MaskRIS: Semantic Distortion-aware Data Augmentation for Referring Image Segmentation

Minhyun Lee, Seungho Lee, Song Park +3

Referring Image Segmentation (RIS) is an advanced vision-language task that involves identifying and segmenting objects within an image as described by free-form text descriptions.…

cs.CV2025

Masking meets Supervision: A Strong Learning Alliance

Byeongho Heo, Taekyung Kim, Sangdoo Yun +1

Pre-training with random masked inputs has emerged as a novel trend in self-supervised training. However, supervised learning still faces a challenge in adopting masking augmentati…

cs.CV2025

Morphing Tokens Draw Strong Masked Image Models

Taekyung Kim, Byeongho Heo, Dongyoon Han

Masked image modeling (MIM) has emerged as a promising approach for pre-training Vision Transformers (ViTs). MIMs predict masked tokens token-wise to recover target signals that ar…