4 papers
MuCo: Multi-turn Contrastive Learning for Multimodal Embedding Model
Geonmo Gu, Byeongho Heo, Jaemyung Yu +7
Universal Multimodal embedding models built on Multimodal Large Language Models (MLLMs) have traditionally employed contrastive learning, which aligns representations of query-targ…
VisualScratchpad: Inference-time Visual Concepts Analysis in Vision Language Models
Hyesu Lim, Jinho Choi, Taekyung Kim +3
High-performing vision language models still produce incorrect answers, yet their failure modes are often difficult to explain. To make model internals more accessible and enable s…
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…
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…