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20182026
most citedTest-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models

112 citations · 423 across the 41 of their papers we have counts for

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Showing 2022Show all

10 papers · 1 filter

cs.LG2022★ 22 cited

Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing

Shengchao Liu, Weili Nie, Chengpeng Wang +6

There is increasing adoption of artificial intelligence in drug discovery. However, existing studies use machine learning to mainly utilize the chemical structures of molecules but…

cs.LG2022★ 17 cited

Fast Sampling of Diffusion Models via Operator Learning

Hongkai Zheng, Weili Nie, Arash Vahdat +2

Diffusion models have found widespread adoption in various areas. However, their sampling process is slow because it requires hundreds to thousands of network evaluations to emulat…

cs.LG2022★ 18 cited

DensePure: Understanding Diffusion Models towards Adversarial Robustness

Chaowei Xiao, Zhongzhu Chen, Kun Jin +6

Diffusion models have been recently employed to improve certified robustness through the process of denoising. However, the theoretical understanding of why diffusion models are ab…

cs.CV2022★ 112 cited

Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models

Manli Shu, Weili Nie, De-An Huang +4

Pre-trained vision-language models (e.g., CLIP) have shown promising zero-shot generalization in many downstream tasks with properly designed text prompts. Instead of relying on ha…

q-bio.QM2022★ 25 cited

State-specific protein-ligand complex structure prediction with a multi-scale deep generative model

Zhuoran Qiao, Weili Nie, Arash Vahdat +2

The binding complexes formed by proteins and small molecule ligands are ubiquitous and critical to life. Despite recent advancements in protein structure prediction, existing algor…

cs.CV2022★ 10 cited

PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition

Jiachen Sun, Weili Nie, Zhiding Yu +2

3D Point cloud is becoming a critical data representation in many real-world applications like autonomous driving, robotics, and medical imaging. Although the success of deep learn…