Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Li Dong

Li Dong

Detecting and Recovering Adversarial Examples from Extracting Non-robust and Highly Predictive Adversarial Perturbations



Mingyu Dong , Jiahao Chen , Diqun Yan , Jingxing Gao , Li Dong , Rangding Wang

* 10 pages 
   Access Paper or Ask Questions

Language Models are General-Purpose Interfaces



Yaru Hao , Haoyu Song , Li Dong , Shaohan Huang , Zewen Chi , Wenhui Wang , Shuming Ma , Furu Wei

Figure 1 for Language Models are General-Purpose Interfaces
Figure 2 for Language Models are General-Purpose Interfaces
Figure 3 for Language Models are General-Purpose Interfaces
Figure 4 for Language Models are General-Purpose Interfaces
* 32 pages. The first three authors contribute equally 
   Access Paper or Ask Questions

VL-BEiT: Generative Vision-Language Pretraining



Hangbo Bao , Wenhui Wang , Li Dong , Furu Wei

Figure 1 for VL-BEiT: Generative Vision-Language Pretraining
Figure 2 for VL-BEiT: Generative Vision-Language Pretraining
Figure 3 for VL-BEiT: Generative Vision-Language Pretraining
Figure 4 for VL-BEiT: Generative Vision-Language Pretraining

   Access Paper or Ask Questions

THE-X: Privacy-Preserving Transformer Inference with Homomorphic Encryption



Tianyu Chen , Hangbo Bao , Shaohan Huang , Li Dong , Binxing Jiao , Daxin Jiang , Haoyi Zhou , Jianxin Li , Furu Wei

* Findings of ACL 2022 
   Access Paper or Ask Questions

Exploiting Constructive Interference for Backscatter Communication Systems



Gu Bowen , Li Dong , Liu Ye , Xu Yongjun

Figure 1 for Exploiting Constructive Interference for Backscatter Communication Systems
Figure 2 for Exploiting Constructive Interference for Backscatter Communication Systems
Figure 3 for Exploiting Constructive Interference for Backscatter Communication Systems
Figure 4 for Exploiting Constructive Interference for Backscatter Communication Systems

   Access Paper or Ask Questions

Prototypical Calibration for Few-shot Learning of Language Models



Zhixiong Han , Yaru Hao , Li Dong , Furu Wei

Figure 1 for Prototypical Calibration for Few-shot Learning of Language Models
Figure 2 for Prototypical Calibration for Few-shot Learning of Language Models
Figure 3 for Prototypical Calibration for Few-shot Learning of Language Models
Figure 4 for Prototypical Calibration for Few-shot Learning of Language Models

   Access Paper or Ask Questions

Visually-Augmented Language Modeling



Weizhi Wang , Li Dong , Hao Cheng , Haoyu Song , Xiaodong Liu , Xifeng Yan , Jianfeng Gao , Furu Wei

Figure 1 for Visually-Augmented Language Modeling
Figure 2 for Visually-Augmented Language Modeling
Figure 3 for Visually-Augmented Language Modeling
Figure 4 for Visually-Augmented Language Modeling

   Access Paper or Ask Questions

Transferability of Adversarial Attacks on Synthetic Speech Detection



Jiacheng Deng , Shunyi Chen , Li Dong , Diqun Yan , Rangding Wang

Figure 1 for Transferability of Adversarial Attacks on Synthetic Speech Detection
Figure 2 for Transferability of Adversarial Attacks on Synthetic Speech Detection
Figure 3 for Transferability of Adversarial Attacks on Synthetic Speech Detection
Figure 4 for Transferability of Adversarial Attacks on Synthetic Speech Detection
* 5 pages, submit to Interspeech2022 
   Access Paper or Ask Questions

Many a little Makes a Mickle: Probing Backscattering Energy Recycling for Backscatter Communications



Gu Bowen , Li Dong , Xu Yongjun , Li Chunguo , Sun Sumei

Figure 1 for Many a little Makes a Mickle: Probing Backscattering Energy Recycling for Backscatter Communications
Figure 2 for Many a little Makes a Mickle: Probing Backscattering Energy Recycling for Backscatter Communications
Figure 3 for Many a little Makes a Mickle: Probing Backscattering Energy Recycling for Backscatter Communications
Figure 4 for Many a little Makes a Mickle: Probing Backscattering Energy Recycling for Backscatter Communications

   Access Paper or Ask Questions
1
2
3
4
5
6
7
>>