1 citations · 1 across the 2 of their papers we have counts for
6 papers
Large Language Model Teaches Visual Students: Cross-Modality Transfer of Fine-Grained Conceptual Knowledge
Thomas Shih-Chao Liang, Zhuoran Yu, Yong Jae Lee
Large Language Models (LLMs) possess broad conceptual knowledge acquired through large-scale text pretraining, yet their potential to supervise models in other modalities remains u…
DAVE: A VLM Vision Encoder for Document Understanding and Web Agents
Brandon Huang, Hang Hua, Zhuoran Yu +3
While Vision-language models (VLMs) have demonstrated remarkable performance across multi-modal tasks, their choice of vision encoders presents a fundamental weakness: their low-le…
See, Hear, and Understand: Benchmarking Audiovisual Human Speech Understanding in Multimodal Large Language Models
Le Thien Phuc Nguyen, Zhuoran Yu, Samuel Low Yu Hang +8
Multimodal large language models (MLLMs) are expected to jointly interpret vision, audio, and language, yet existing video benchmarks rarely assess fine-grained reasoning about hum…
How Multimodal LLMs Solve Image Tasks: A Lens on Visual Grounding, Task Reasoning, and Answer Decoding
Zhuoran Yu, Yong Jae Lee
Multimodal Large Language Models (MLLMs) have demonstrated strong performance across a wide range of vision-language tasks, yet their internal processing dynamics remain underexplo…
CuRe: Cultural Gaps in the Long Tail of Text-to-Image Systems
Aniket Rege, Zinnia Nie, Mahesh Ramesh +5
Popular text-to-image (T2I) systems are trained on web-scraped data, which is heavily Amero and Euro-centric, underrepresenting the cultures of the Global South. To analyze these b…
LASER: Lip Landmark Assisted Speaker Detection for Robustness
Le Thien Phuc Nguyen, Zhuoran Yu, Yong Jae Lee
Active Speaker Detection (ASD) aims to identify who is speaking in complex visual scenes. While humans naturally rely on lip-audio synchronization, existing ASD models often miscla…