activity
20232026
most citedA Survey on Multimodal Large Language Models for Autonomous Driving

27 citations · 31 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Decoding Children's Gait Behavior

Yifan Shen, Boyi Li, Meihuan Huang +12

We introduce a new problem domain for human action recognition: the fine-grained analysis of children's gait behaviors from standard RGB video. We specifically target the ambulator…

cs.CV2026

Toward Cognitive Supersensing in Multimodal Large Language Model

Boyi Li, Yifan Shen, Yuanzhe Liu +12

Multimodal Large Language Models (MLLMs) have achieved remarkable success in open-vocabulary perceptual tasks, yet their ability to solve complex cognitive problems remains limited…

astro-ph.IM2025★ 1 cited

AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy

Jinghang Shi, Xiaoyu Tang, Yang Huang +4

Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…

cs.CV2024★ 2 cited

Medical Video Generation for Disease Progression Simulation

Xu Cao, Kaizhao Liang, Kuei-Da Liao +7

Modeling disease progression is crucial for improving the quality and efficacy of clinical diagnosis and prognosis, but it is often hindered by a lack of longitudinal medical image…

cs.CV2024

What is the Visual Cognition Gap between Humans and Multimodal LLMs?

Xu Cao, Yifan Shen, Bolin Lai +8

Recently, Multimodal Large Language Models (MLLMs) and Vision Language Models (VLMs) have shown great promise in language-guided perceptual tasks such as recognition, segmentation,…

cs.AI2023★ 27 cited

A Survey on Multimodal Large Language Models for Autonomous Driving

Can Cui, Yunsheng Ma, Xu Cao +18

With the emergence of Large Language Models (LLMs) and Vision Foundation Models (VFMs), multimodal AI systems benefiting from large models have the potential to equally perceive th…

eess.IV2023★ 1 cited

PIE: Simulating Disease Progression via Progressive Image Editing

Kaizhao Liang, Xu Cao, Kuei-Da Liao +6

Disease progression simulation is a crucial area of research that has significant implications for clinical diagnosis, prognosis, and treatment. One major challenge in this field i…