849 citations · 2k across the 67 of their papers we have counts for
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MedAutoCorrect: Image-Conditioned Autocorrection in Medical Reporting
Arnold Caleb Asiimwe, Dídac Surís, Pranav Rajpurkar +1
In medical reporting, the accuracy of radiological reports, whether generated by humans or machine learning algorithms, is critical. We tackle a new task in this paper: image-condi…
Dreamitate: Real-World Visuomotor Policy Learning via Video Generation
Junbang Liang, Ruoshi Liu, Ege Ozguroglu +5
A key challenge in manipulation is learning a policy that can robustly generalize to diverse visual environments. A promising mechanism for learning robust policies is to leverage…
Generative Camera Dolly: Extreme Monocular Dynamic Novel View Synthesis
Basile Van Hoorick, Rundi Wu, Ege Ozguroglu +6
Accurate reconstruction of complex dynamic scenes from just a single viewpoint continues to be a challenging task in computer vision. Current dynamic novel view synthesis methods t…
SelfIE: Self-Interpretation of Large Language Model Embeddings
Haozhe Chen, Carl Vondrick, Chengzhi Mao
How do large language models (LLMs) obtain their answers? The ability to explain and control an LLM's reasoning process is key for reliability, transparency, and future model devel…
PaperBot: Learning to Design Real-World Tools Using Paper
Ruoshi Liu, Junbang Liang, Sruthi Sudhakar +4
Paper is a cheap, recyclable, and clean material that is often used to make practical tools. Traditional tool design either relies on simulation or physical analysis, which is ofte…
GES: Generalized Exponential Splatting for Efficient Radiance Field Rendering
Abdullah Hamdi, Luke Melas-Kyriazi, Jinjie Mai +5
Advancements in 3D Gaussian Splatting have significantly accelerated 3D reconstruction and generation. However, it may require a large number of Gaussians, which creates a substant…
pix2gestalt: Amodal Segmentation by Synthesizing Wholes
Ege Ozguroglu, Ruoshi Liu, Dídac Surís +4
We introduce pix2gestalt, a framework for zero-shot amodal segmentation, which learns to estimate the shape and appearance of whole objects that are only partially visible behind o…
Raidar: geneRative AI Detection viA Rewriting
Chengzhi Mao, Carl Vondrick, Hao Wang +1
We find that large language models (LLMs) are more likely to modify human-written text than AI-generated text when tasked with rewriting. This tendency arises because LLMs often pe…