16 citations · 28 across the 25 of their papers we have counts for
5 papers · 1 filter
VIEScore: Towards Explainable Metrics for Conditional Image Synthesis Evaluation
Max Ku, Dongfu Jiang, Cong Wei +2
In the rapidly advancing field of conditional image generation research, challenges such as limited explainability lie in effectively evaluating the performance and capabilities of…
UniIR: Training and Benchmarking Universal Multimodal Information Retrievers
Cong Wei, Yang Chen, Haonan Chen +5
Existing information retrieval (IR) models often assume a homogeneous format, limiting their applicability to diverse user needs, such as searching for images with text description…
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
Xiang Yue, Yuansheng Ni, Kai Zhang +19
We introduce MMMU: a new benchmark designed to evaluate multimodal models on massive multi-discipline tasks demanding college-level subject knowledge and deliberate reasoning. MMMU…
DreamEdit: Subject-driven Image Editing
Tianle Li, Max Ku, Cong Wei +1
Subject-driven image generation aims at generating images containing customized subjects, which has recently drawn enormous attention from the research community. However, the prev…
Sparsifiner: Learning Sparse Instance-Dependent Attention for Efficient Vision Transformers
Cong Wei, Brendan Duke, Ruowei Jiang +3
Vision Transformers (ViT) have shown their competitive advantages performance-wise compared to convolutional neural networks (CNNs) though they often come with high computational c…