Frederick Liu - RankMe

44 papers A* 8A 1B 1C 1Journal 24Unranked 9

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	"We Need Structured Output": Towards User-centered Constraints on Large Language Model Output. CHI Extended Abstracts Michael Xieyang Liu, Frederick Liu, Alexander J. Fiannaca, Terry Koo, Lucas Dixon, Michael Terry, Carrie J. Cai
2024	J	`jnl`	"We Need Structured Output": Towards User-centered Constraints on Large Language Model Output. CoRR Michael Xieyang Liu, Frederick Liu, Alexander J. Fiannaca, Terry Koo, Lucas Dixon, Michael Terry, Carrie J. Cai
2024	J	`jnl`	Automata-based constraints for language model decoding. CoRR Terry Koo, Frederick Liu, Luheng He
2024	A*	`conf`	SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. ICRA 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
2023	A*	`conf`	Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation. ICLR Ziqi Wang, Yuexin Wu, Frederick Liu, Daogao Liu, Le Hou, Hongkun Yu, Jing Li, Heng Ji
2023	A*	`conf`	Dense-Exponential Random Features: Sharp Positive Estimators of the Gaussian Kernel. NeurIPS Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
2023	J	`jnl`	FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features. CoRR Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
2023	J	`jnl`	Gradient-Based Automated Iterative Recovery for Parameter-Efficient Tuning. CoRR Maximilian Mozes, Tolga Bolukbasi, Ann Yuan, Frederick Liu, Nithum Thain, Lucas Dixon
2023	C	`conf`	Improving Multilingual and Code-Switching ASR Using Large Language Model Generated Text. ASRU Ke Hu, Tara N. Sainath, Bo Li, Yu Zhang, Yong Cheng, Tao Wang, Yujing Zhang, Frederick Liu
2023	J	`jnl`	Non-Intrusive Adaptation: Input-Centric Parameter-efficient Fine-Tuning for Versatile Multimodal Modeling. CoRR Yaqing Wang, Jialin Wu, Tanmaya Dabral, Jiageng Zhang, Geoff Brown, Chun-Ta Lu, Frederick Liu, Yi Liang, Bo Pang, Michael Bendersky, Radu Soricut
2023	J	`jnl`	SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention. CoRR 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
2023	J	`jnl`	UT5: Pretraining Non autoregressive T5 with unrolled denoising. CoRR Mahmoud G. Salem, Jiayu Ye, Chu-Cheng Lin, Frederick Liu
2023	J	`jnl`	Using Foundation Models to Detect Policy Violations with Minimal Supervision. CoRR Sid Mittal, Vineet Gupta, Frederick Liu, Mukund Sundararajan
2022	J	`jnl`	Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation. CoRR Ziqi Wang, Yuexin Wu, Frederick Liu, Daogao Liu, Le Hou, Hongkun Yu, Jing Li, Heng Ji
2022	A*	`conf`	Chefs' Random Tables: Non-Trigonometric Random Features. NeurIPS Valerii Likhosherstov, Krzysztof Marcin Choromanski, Kumar Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
2022	J	`jnl`	Chefs' Random Tables: Non-Trigonometric Random Features. CoRR Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey, Frederick Liu, Tamás Sarlós, Adrian Weller
2022	J	`jnl`	DETR++: Taming Your Multi-Scale Detection Transformer. CoRR Chi Zhang, Lijuan Liu, Xiaoxue Zang, Frederick Liu, Hao Zhang, Xinying Song, Jindong Chen
2022	—	`conf`	Differentially-Private "Draw and Discard" Machine Learning: Training Distributed Model from Enormous Crowds. CSCML Vasyl Pihur, Aleksandra Korolova, Frederick Liu, Subhash Sankuratripati, Moti Yung, Dachuan Huang, Ruogu Zeng
2022	A*	`conf`	First is Better Than Last for Language Data Influence. NeurIPS Chih-Kuan Yeh, Ankur Taly, Mukund Sundararajan, Frederick Liu, Pradeep Ravikumar
2022	J	`jnl`	First is Better Than Last for Training Data Influence. CoRR Chih-Kuan Yeh, Ankur Taly, Mukund Sundararajan, Frederick Liu, Pradeep Ravikumar
2022	A	`conf`	Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations. AISTATS Chih-Kuan Yeh, Kuan-Yun Lee, Frederick Liu, Pradeep Ravikumar
2022	J	`jnl`	Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations. CoRR Chih-Kuan Yeh, Kuan-Yun Lee, Frederick Liu, Pradeep Ravikumar
2022	—	`conf`	Towards Tracing Knowledge in Language Models Back to the Training Data. EMNLP (Findings) Ekin Akyürek, Tolga Bolukbasi, Frederick Liu, Binbin Xiong, Ian Tenney, Jacob Andreas, Kelvin Guu
2022	J	`jnl`	Tracing Knowledge in Language Models Back to the Training Data. CoRR Ekin Akyürek, Tolga Bolukbasi, Frederick Liu, Binbin Xiong, Ian Tenney, Jacob Andreas, Kelvin Guu
2021	A*	`conf`	Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles. NeurIPS Jiefeng Chen, Frederick Liu, Besim Avci, Xi Wu, Yingyu Liang, Somesh Jha
2021	J	`jnl`	Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles. CoRR Jiefeng Chen, Frederick Liu, Besim Avci, Xi Wu, Yingyu Liang, Somesh Jha
2021	J	`jnl`	EncT5: Fine-tuning T5 Encoder for Non-autoregressive Tasks. CoRR Frederick Liu, Siamak Shakeri, Hongkun Yu, Jing Li
2021	J	`jnl`	Leveraging redundancy in attention with Reuse Transformers. CoRR Srinadh Bhojanapalli, Ayan Chakrabarti, Andreas Veit, Michal Lukasik, Himanshu Jain, Frederick Liu, Yin-Wen Chang, Sanjiv Kumar
2020	A*	`conf`	Estimating Training Data Influence by Tracing Gradient Descent. NeurIPS Garima Pruthi, Frederick Liu, Satyen Kale, Mukund Sundararajan
2020	J	`jnl`	Estimating Training Data Influence by Tracking Gradient Descent. CoRR Garima Pruthi, Frederick Liu, Mukund Sundararajan, Satyen Kale
2020	J	`jnl`	The Penalty Imposed by Ablated Data Augmentation. CoRR Frederick Liu, Amir Najmi, Mukund Sundararajan
2019	J	`jnl`	Analyzing Privacy Policies at Scale: From Crowdsourcing to Automated Annotations. ACM Trans. Web 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
2019	—	`conf`	Incorporating Priors with Feature Attribution on Text Classification. ACL (1) Frederick Liu, Besim Avci
2019	J	`jnl`	Incorporating Priors with Feature Attribution on Text Classification. CoRR Frederick Liu, Besim Avci
2018	J	`jnl`	Differentially-Private "Draw and Discard" Machine Learning. CoRR Vasyl Pihur, Aleksandra Korolova, Frederick Liu, Subhash Sankuratripati, Moti Yung, Dachuan Huang, Ruogu Zeng
2018	—	`conf`	Handling Homographs in Neural Machine Translation. NAACL-HLT Frederick Liu, Han Lu, Graham Neubig
2017	J	`jnl`	Handling Homographs in Neural Machine Translation. CoRR Frederick Liu, Han Lu, Graham Neubig
2017	—	`conf`	Learning Character-level Compositionality with Visual Features. ACL (1) Frederick Liu, Han Lu, Chieh Lo, Graham Neubig
2017	J	`jnl`	Learning Character-level Compositionality with Visual Features. CoRR Frederick Liu, Han Lu, Chieh Lo, Graham Neubig
2016	—	`conf`	Analyzing Vocabulary Intersections of Expert Annotations and Topic Models for Data Practices in Privacy Policies. AAAI Fall Symposia Frederick Liu, Shomir Wilson, Florian Schaub, Norman M. Sadeh
2016	—	`conf`	Attention-based Multimodal Neural Machine Translation. WMT Po-Yao Huang, Frederick Liu, Sz-Rung Shiang, Jean Oh, Chris Dyer
2016	A*	`conf`	Crowdsourcing Annotations for Websites' Privacy Policies: Can It Really Work? WWW Shomir Wilson, Florian Schaub, Rohan Ramanath, Norman M. Sadeh, Fei Liu, Noah A. Smith, Frederick Liu
2016	—	`conf`	The Creation and Analysis of a Website Privacy Policy Corpus. ACL (1) 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
2014	B	`conf`	Learning Pronunciation and Accent from The Crowd. HCOMP Frederick Liu, Jeremy Chiaming Yang, Jane Yung-jen Hsu