9 papers
Reducing Peak Memory Usage for Modern Multimodal Large Language Model Pipelines
Junwan Kim, Hyunkyung Bae
Multimodal large language models (MLLMs) have recently demonstrated strong capabilities in understanding and generating responses from diverse visual inputs, including high-resolut…
Better Source, Better Flow: Learning Condition-Dependent Source Distribution for Flow Matching
Junwan Kim, Jiho Park, Seonghu Jeon +1
Flow matching has recently emerged as a promising alternative to diffusion-based generative models, particularly for text-to-image generation. Despite its flexibility in allowing a…
Visual Representation Alignment for Multimodal Large Language Models
Heeji Yoon, Jaewoo Jung, Junwan Kim +10
Multimodal large language models (MLLMs) trained with visual instruction tuning have achieved strong performance across diverse tasks, yet they remain limited in vision-centric tas…
V.I.P. : Iterative Online Preference Distillation for Efficient Video Diffusion Models
Jisoo Kim, Wooseok Seo, Junwan Kim +3
With growing interest in deploying text-to-video (T2V) models in resource-constrained environments, reducing their high computational cost has become crucial, leading to extensive…
URECA: Unique Region Caption Anything
Sangbeom Lim, Junwan Kim, Heeji Yoon +2
Region-level captioning aims to generate natural language descriptions for specific image regions while highlighting their distinguishing features. However, existing methods strugg…
DisCoRD: Discrete Tokens to Continuous Motion via Rectified Flow Decoding
Jungbin Cho, Junwan Kim, Jisoo Kim +5
Human motion is inherently continuous and dynamic, posing significant challenges for generative models. While discrete generation methods are widely used, they suffer from limited…
TWLV-I: Analysis and Insights from Holistic Evaluation on Video Foundation Models
Hyeongmin Lee, Jin-Young Kim, Kyungjune Baek +18
In this work, we discuss evaluating video foundation models in a fair and robust manner. Unlike language or image foundation models, many video foundation models are evaluated with…
AVIN-Chat: An Audio-Visual Interactive Chatbot System with Emotional State Tuning
Chanhyuk Park, Jungbin Cho, Junwan Kim +3
This work presents an audio-visual interactive chatbot (AVIN-Chat) system that allows users to have face-to-face conversations with 3D avatars in real-time. Compared to the previou…
Pegasus-v1 Technical Report
Raehyuk Jung, Hyojun Go, Jaehyuk Yi +41
This technical report introduces Pegasus-1, a multimodal language model specialized in video content understanding and interaction through natural language. Pegasus-1 is designed t…