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A Tool Bottleneck Framework for Clinically-Informed and Interpretable Medical Image Understanding
Christina Liu, Alan Q. Wang, Joy Hsu +2
Recent tool-use frameworks powered by vision-language models (VLMs) improve image understanding by grounding model predictions with specialized tools. Broadly, these frameworks lev…
A Matter of Interest: Understanding Interestingness of Math Problems in Humans and Language Models
Shubhra Mishra, Yuka Machino, Gabriel Poesia +9
The evolution of mathematics is shaped importantly by interestingness: researchers choose which problems to pursue, and students choose which problems to engage with, based on expe…
From Programs to Poses: Factored Real-World Scene Generation via Learned Program Libraries
Joy Hsu, Emily Jin, Jiajun Wu +1
Real-world scenes, such as those in ScanNet, are difficult to capture, with highly limited data available. Generating realistic scenes with varied object poses remains an open and…
Explain Before You Answer: A Survey on Compositional Visual Reasoning
Fucai Ke, Joy Hsu, Zhixi Cai +10
Compositional visual reasoning has emerged as a key research frontier in multimodal AI, aiming to endow machines with the human-like ability to decompose visual scenes, ground inte…
Predicate Hierarchies Improve Few-Shot State Classification
Emily Jin, Joy Hsu, Jiajun Wu
State classification of objects and their relations is core to many long-horizon tasks, particularly in robot planning and manipulation. However, the combinatorial explosion of pos…