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20212026
most citedRADAR: Robust AI-Text Detection via Adversarial Learning

29 citations · 64 across the 17 of their papers we have counts for

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Showing 2022Show all

8 papers · 1 filter

cs.CV2022

How to Backdoor Diffusion Models?

Sheng-Yen Chou, Pin-Yu Chen, Tsung-Yi Ho

Diffusion models are state-of-the-art deep learning empowered generative models that are trained based on the principle of learning forward and reverse diffusion processes via prog…

cs.CV2022

When Neural Networks Fail to Generalize? A Model Sensitivity Perspective

Jiajin Zhang, Hanqing Chao, Amit Dhurandhar +4

Domain generalization (DG) aims to train a model to perform well in unseen domains under different distributions. This paper considers a more realistic yet more challenging scenari…

cs.LG2022

NCTV: Neural Clamping Toolkit and Visualization for Neural Network Calibration

Lei Hsiung, Yung-Chen Tang, Pin-Yu Chen +1

With the advancement of deep learning technology, neural networks have demonstrated their excellent ability to provide accurate predictions in many tasks. However, a lack of consid…

cs.LG2022★ 1 cited

SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data

Ching-Yun Ko, Pin-Yu Chen, Jeet Mohapatra +2

Recent success in fine-tuning large models, that are pretrained on broad data at scale, on downstream tasks has led to a significant paradigm shift in deep learning, from task-cent…

q-bio.BM2022★ 9 cited

Reprogramming Pretrained Language Models for Antibody Sequence Infilling

Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen +4

Antibodies comprise the most versatile class of binding molecules, with numerous applications in biomedicine. Computational design of antibodies involves generating novel and diver…

cs.LG2022★ 9 cited

Active Sampling of Multiple Sources for Sequential Estimation

Arpan Mukherjee, Ali Tajer, Pin-Yu Chen +1

Consider processes, each generating a sequence of identical and independent random variables. The probability measures of these processes have random parameters that must be es…

cs.LG2022★ 5 cited

Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM

Chulin Xie, Pin-Yu Chen, Qinbin Li +3

Federated learning (FL) enables distributed resource-constrained devices to jointly train shared models while keeping the training data local for privacy purposes. Vertical FL (VFL…

cs.LG2022

Learning Geometrically Disentangled Representations of Protein Folding Simulations

N. Joseph Tatro, Payel Das, Pin-Yu Chen +2

Massive molecular simulations of drug-target proteins have been used as a tool to understand disease mechanism and develop therapeutics. This work focuses on learning a generative…