2 citations · 2 across the 8 of their papers we have counts for
4 papers · 1 filter
What Happens When: Learning Temporal Orders of Events in Videos
Daechul Ahn, Yura Choi, Hyeonbeom Choi +3
Video Large Multimodal Models (VLMMs) have shown impressive performance in video understanding, yet their ability to accurately capture the temporal order of multiple events remain…
ISR-DPO: Aligning Large Multimodal Models for Videos by Iterative Self-Retrospective DPO
Daechul Ahn, Yura Choi, San Kim +3
Iterative self-improvement, a concept extending beyond personal growth, has found powerful applications in machine learning, particularly in transforming weak models into strong on…
Tuning Large Multimodal Models for Videos using Reinforcement Learning from AI Feedback
Daechul Ahn, Yura Choi, Youngjae Yu +2
Recent advancements in large language models have influenced the development of video large multimodal models (VLMMs). The previous approaches for VLMMs involved Supervised Fine-Tu…
Story Visualization by Online Text Augmentation with Context Memory
Daechul Ahn, Daneul Kim, Gwangmo Song +4
Story visualization (SV) is a challenging text-to-image generation task for the difficulty of not only rendering visual details from the text descriptions but also encoding a long-…