1 citations · 1 across the 3 of their papers we have counts for
7 papers
ReFocus: Visual Editing as a Chain of Thought for Structured Image Understanding
Xingyu Fu, Minqian Liu, Zhengyuan Yang +6
Structured image understanding, such as interpreting tables and charts, requires strategically refocusing across various structures and texts within an image, forming a reasoning s…
MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding
Fei Wang, Xingyu Fu, James Y. Huang +18
We introduce MuirBench, a comprehensive benchmark that focuses on robust multi-image understanding capabilities of multimodal LLMs. MuirBench consists of 12 diverse multi-image tas…
FamiCom: Further Demystifying Prompts for Language Models with Task-Agnostic Performance Estimation
Bangzheng Li, Ben Zhou, Xingyu Fu +3
Language models have shown impressive in-context-learning capabilities, which allow them to benefit from input prompts and perform better on downstream end tasks. Existing works in…
Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models
Yushi Hu, Weijia Shi, Xingyu Fu +5
Humans draw to facilitate reasoning: we draw auxiliary lines when solving geometry problems; we mark and circle when reasoning on maps; we use sketches to amplify our ideas and rel…
Commonsense-T2I Challenge: Can Text-to-Image Generation Models Understand Commonsense?
Xingyu Fu, Muyu He, Yujie Lu +2
We present a novel task and benchmark for evaluating the ability of text-to-image(T2I) generation models to produce images that align with commonsense in real life, which we call C…
BIRD: A Trustworthy Bayesian Inference Framework for Large Language Models
Yu Feng, Ben Zhou, Weidong Lin +1
Predictive models often need to work with incomplete information in real-world tasks. Consequently, they must provide reliable probability or confidence estimation, especially in l…