Learning Pronunciation and Accent from The Crowd. - Frederick Liu; Jeremy Chiaming Yang; Jane Yung-jen Hsu (HCOMP, 2014)

Analyzing Vocabulary Intersections of Expert Annotations and Topic Models for Data Practices in Privacy Policies. - Frederick Liu; Shomir Wilson; Florian Schaub; Norman M. Sadeh (AAAI Fall Symposia, 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; et al. (ACL (1), 2016)

Attention-based Multimodal Neural Machine Translation. - Po-Yao Huang 001; Frederick Liu; Sz-Rung Shiang; Jean Oh; Chris Dyer (WMT, 2016)

Crowdsourcing Annotations for Websites' Privacy Policies: Can It Really Work? - Shomir Wilson; Florian Schaub; Rohan Ramanath; Norman M. Sadeh; Fei Liu 004; Noah A. Smith; Frederick Liu (WWW, 2016)

Learning Character-level Compositionality with Visual Features. - Frederick Liu; Han Lu; Chieh Lo; Graham Neubig (ACL (1), 2017)

Handling Homographs in Neural Machine Translation. - Frederick Liu; Han Lu; Graham Neubig (NAACL-HLT, 2018)

Differentially-Private "Draw and Discard" Machine Learning. - Vasyl Pihur; Aleksandra Korolova; Frederick Liu; Subhash Sankuratripati; Moti Yung; Dachuan Huang; Ruogu Zeng (CoRR, 2018)

Incorporating Priors with Feature Attribution on Text Classification. - Frederick Liu; Besim Avci (ACL (1), 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 004; Norman M. Sadeh; Noah A. Smith (ACM Trans. Web, 2019)

Estimating Training Data Influence by Tracing Gradient Descent. - Garima Pruthi; Frederick Liu; Satyen Kale; Mukund Sundararajan (NeurIPS, 2020)

Estimating Training Data Influence by Tracking Gradient Descent. - Garima Pruthi; Frederick Liu; Mukund Sundararajan; Satyen Kale (CoRR, 2020)

The Penalty Imposed by Ablated Data Augmentation. - Frederick Liu; Amir Najmi; Mukund Sundararajan (CoRR, 2020)

Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles. - Jiefeng Chen 001; Frederick Liu; Besim Avci; Xi Wu 001; Yingyu Liang; Somesh Jha (NeurIPS, 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)

EncT5: Fine-tuning T5 Encoder for Non-autoregressive Tasks. - Frederick Liu; Siamak Shakeri; Hongkun Yu 001; Jing Li 049 (CoRR, 2021)

Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations. - Chih-Kuan Yeh; Kuan-Yun Lee; Frederick Liu; Pradeep Ravikumar (AISTATS, 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 (CSCML, 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 (EMNLP (Findings), 2022)

Chefs' Random Tables: Non-Trigonometric Random Features. - Valerii Likhosherstov; Krzysztof Marcin Choromanski; Kumar Avinava Dubey; Frederick Liu; Tamás Sarlós; Adrian Weller (NeurIPS, 2022)

First is Better Than Last for Language Data Influence. - Chih-Kuan Yeh; Ankur Taly; Mukund Sundararajan; Frederick Liu; Pradeep Ravikumar (NeurIPS, 2022)

First is Better Than Last for Training Data Influence. - Chih-Kuan Yeh; Ankur Taly; Mukund Sundararajan; Frederick Liu; Pradeep Ravikumar (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)

DETR++: Taming Your Multi-Scale Detection Transformer. - Chi Zhang; Lijuan Liu; Xiaoxue Zang; Frederick Liu; Hao Zhang; Xinying Song; Jindong Chen (CoRR, 2022)

Improving Multilingual and Code-Switching ASR Using Large Language Model Generated Text. - Ke Hu; Tara N. Sainath; Bo Li 028; Yu Zhang 033; Yong Cheng; Tao Wang; Yujing Zhang; Frederick Liu (ASRU, 2023)

Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation. - Ziqi Wang 003; Yuexin Wu; Frederick Liu; Daogao Liu; Le Hou; Hongkun Yu 001; Jing Li 049; Heng Ji 001 (ICLR, 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 (NeurIPS, 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)

Gradient-Based Automated Iterative Recovery for Parameter-Efficient Tuning. - Maximilian Mozes; Tolga Bolukbasi; Ann Yuan; Frederick Liu; Nithum Thain; Lucas Dixon (CoRR, 2023)

Using Foundation Models to Detect Policy Violations with Minimal Supervision. - Sid Mittal; Vineet Gupta 001; Frederick Liu; Mukund Sundararajan (CoRR, 2023)

Non-Intrusive Adaptation: Input-Centric Parameter-efficient Fine-Tuning for Versatile Multimodal Modeling. - Yaqing Wang 007; Jialin Wu; Tanmaya Dabral; Jiageng Zhang; Geoff Brown; Chun-Ta Lu; Frederick Liu; Yi Liang; Bo Pang 001; Michael Bendersky; Radu Soricut (CoRR, 2023)

UT5: Pretraining Non autoregressive T5 with unrolled denoising. - Mahmoud G. Salem; Jiayu Ye; Chu-Cheng Lin; Frederick Liu (CoRR, 2023)

"We Need Structured Output": Towards User-centered Constraints on Large Language Model Output. - Michael Xieyang Liu; Frederick Liu; Alexander J. Fiannaca; Terry Koo; Lucas Dixon; Michael Terry; Carrie J. Cai (CHI Extended Abstracts, 2024)

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 006; Frederick Liu; Vikas Sindhwani; Quan Vuong; Tamás Sarlós; Ken Oslund; et al. (ICRA, 2024)

Automata-based constraints for language model decoding. - Terry Koo; Frederick Liu; Luheng He (CoRR, 2024)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)