Frederick Liu

According to our database, Frederick Liu authored at least 33 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention.

Isabel Leal, Krzysztof Choromanski, Deepali Jain, Avinava Dubey, Jake Varley, Michael S. Ryoo, Yao Lu, Frederick Liu, Vikas Sindhwani, Quan Vuong, Tamás Sarlós, Ken Oslund, Karol Hausman, Kanishka Rao

CoRR, 2023

UT5: Pretraining Non autoregressive T5 with unrolled denoising.

Mahmoud G. Salem, Jiayu Ye, Chu-Cheng Lin, Frederick Liu

CoRR, 2023

Non-Intrusive Adaptation: Input-Centric Parameter-efficient Fine-Tuning for Versatile Multimodal Modeling.

Yaqing Wang, Jialin Wu, Tanmaya Dabral, Jiageng Zhang, Geoff Brown, Chun-Ta Lu, Frederick Liu, Yi Liang, Bo Pang, Michael Bendersky, Radu Soricut

CoRR, 2023

Using Foundation Models to Detect Policy Violations with Minimal Supervision.

Sid Mittal, Vineet Gupta, Frederick Liu, Mukund Sundararajan

CoRR, 2023

Gradient-Based Automated Iterative Recovery for Parameter-Efficient Tuning.

Maximilian Mozes, Tolga Bolukbasi, Ann Yuan, Frederick Liu, Nithum Thain, Lucas Dixon

CoRR, 2023

FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features.

Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller

CoRR, 2023

Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel.

Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation.

Ziqi Wang, Yuexin Wu, Frederick Liu, Daogao Liu, Le Hou, Hongkun Yu, Jing Li, Heng Ji

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Improving Multilingual and Code-Switching ASR Using Large Language Model Generated Text.

Ke Hu, Tara N. Sainath, Bo Li, Yu Zhang, Yong Cheng, Tao Wang, Yujing Zhang, Frederick Liu

Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2023

2022

DETR++: Taming Your Multi-Scale Detection Transformer.

Chi Zhang, Lijuan Liu, Xiaoxue Zang, Frederick Liu, Hao Zhang, Xinying Song, Jindong Chen

CoRR, 2022

Tracing Knowledge in Language Models Back to the Training Data.

Ekin Akyürek, Tolga Bolukbasi, Frederick Liu, Binbin Xiong, Ian Tenney, Jacob Andreas, Kelvin Guu

CoRR, 2022

First is Better Than Last for Training Data Influence.

Chih-Kuan Yeh, Ankur Taly, Mukund Sundararajan, Frederick Liu, Pradeep Ravikumar

CoRR, 2022

First is Better Than Last for Language Data Influence.

Chih-Kuan Yeh, Ankur Taly, Mukund Sundararajan, Frederick Liu, Pradeep Ravikumar

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Chefs' Random Tables: Non-Trigonometric Random Features.

Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Towards Tracing Knowledge in Language Models Back to the Training Data.

Ekin Akyürek, Tolga Bolukbasi, Frederick Liu, Binbin Xiong, Ian Tenney, Jacob Andreas, Kelvin Guu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Differentially-Private "Draw and Discard" Machine Learning: Training Distributed Model from Enormous Crowds.

Vasyl Pihur, Aleksandra Korolova, Frederick Liu, Subhash Sankuratripati, Moti Yung, Dachuan Huang, Ruogu Zeng

Proceedings of the Cyber Security, Cryptology, and Machine Learning, 2022

Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations.

Chih-Kuan Yeh, Kuan-Yun Lee, Frederick Liu, Pradeep Ravikumar

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

EncT5: Fine-tuning T5 Encoder for Non-autoregressive Tasks.

Frederick Liu, Siamak Shakeri, Hongkun Yu, Jing Li

CoRR, 2021

Leveraging redundancy in attention with Reuse Transformers.

Srinadh Bhojanapalli, Ayan Chakrabarti, Andreas Veit, Michal Lukasik, Himanshu Jain, Frederick Liu, Yin-Wen Chang, Sanjiv Kumar

CoRR, 2021

Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles.

Jiefeng Chen, Frederick Liu, Besim Avci, Xi Wu, Yingyu Liang, Somesh Jha

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

The Penalty Imposed by Ablated Data Augmentation.

Frederick Liu, Amir Najmi, Mukund Sundararajan

CoRR, 2020

Estimating Training Data Influence by Tracking Gradient Descent.

Garima Pruthi, Frederick Liu, Mukund Sundararajan, Satyen Kale

CoRR, 2020

Estimating Training Data Influence by Tracing Gradient Descent.

Garima Pruthi, Frederick Liu, Satyen Kale, Mukund Sundararajan

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Analyzing Privacy Policies at Scale: From Crowdsourcing to Automated Annotations.

Shomir Wilson, Florian Schaub, Frederick Liu, Kanthashree Mysore Sathyendra, Daniel Smullen, Sebastian Zimmeck, Rohan Ramanath, Peter Story, Fei Liu, Norman M. Sadeh, Noah A. Smith

ACM Trans. Web, 2019

Incorporating Priors with Feature Attribution on Text Classification.

Frederick Liu, Besim Avci

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Differentially-Private "Draw and Discard" Machine Learning.

Vasyl Pihur, Aleksandra Korolova, Frederick Liu, Subhash Sankuratripati, Moti Yung, Dachuan Huang, Ruogu Zeng

CoRR, 2018

Handling Homographs in Neural Machine Translation.

Frederick Liu, Han Lu, Graham Neubig

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

2017

Learning Character-level Compositionality with Visual Features.

Frederick Liu, Han Lu, Chieh Lo, Graham Neubig

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

Crowdsourcing Annotations for Websites' Privacy Policies: Can It Really Work?

Shomir Wilson, Florian Schaub, Rohan Ramanath, Norman M. Sadeh, Fei Liu, Noah A. Smith, Frederick Liu

Proceedings of the 25th International Conference on World Wide Web, 2016

Attention-based Multimodal Neural Machine Translation.

Po-Yao Huang, Frederick Liu, Sz-Rung Shiang, Jean Oh, Chris Dyer

Proceedings of the First Conference on Machine Translation, 2016

The Creation and Analysis of a Website Privacy Policy Corpus.

Shomir Wilson, Florian Schaub, Aswarth Abhilash Dara, Frederick Liu, Sushain Cherivirala, Pedro Giovanni Leon, Mads Schaarup Andersen, Sebastian Zimmeck, Kanthashree Mysore Sathyendra, N. Cameron Russell, Thomas B. Norton, Eduard H. Hovy, Joel R. Reidenberg, Norman M. Sadeh

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Analyzing Vocabulary Intersections of Expert Annotations and Topic Models for Data Practices in Privacy Policies.

Frederick Liu, Shomir Wilson, Florian Schaub, Norman M. Sadeh

Proceedings of the 2016 AAAI Fall Symposia, Arlington, Virginia, USA, November 17-19, 2016, 2016

2014

Learning Pronunciation and Accent from The Crowd.

Frederick Liu, Jeremy Chiaming Yang, Jane Yung-jen Hsu

Proceedings of the Seconf AAAI Conference on Human Computation and Crowdsourcing, 2014