Yuntian Deng

According to our database, Yuntian Deng authored at least 48 papers between 2015 and 2024.

Collaborative distances:

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

2024

WildHallucinations: Evaluating Long-form Factuality in LLMs with Real-World Entity Queries.

Wenting Zhao, Tanya Goyal, Yu Ying Chiu, Liwei Jiang, Benjamin Newman, Abhilasha Ravichander, Khyathi Raghavi Chandu, Ronan Le Bras, Claire Cardie, Yuntian Deng, Yejin Choi

CoRR, 2024

Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing.

Zhangchen Xu, Fengqing Jiang, Luyao Niu, Yuntian Deng, Radha Poovendran, Yejin Choi, Bill Yuchen Lin

CoRR, 2024

MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures.

Jinjie Ni, Fuzhao Xue, Xiang Yue, Yuntian Deng, Mahir Shah, Kabir Jain, Graham Neubig, Yang You

CoRR, 2024

WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild.

Bill Yuchen Lin, Yuntian Deng, Khyathi Raghavi Chandu, Faeze Brahman, Abhilasha Ravichander, Valentina Pyatkin, Nouha Dziri, Ronan Le Bras, Yejin Choi

CoRR, 2024

From Explicit CoT to Implicit CoT: Learning to Internalize CoT Step by Step.

Yuntian Deng, Yejin Choi, Stuart M. Shieber

CoRR, 2024

WildChat: 1M ChatGPT Interaction Logs in the Wild.

Wenting Zhao, Xiang Ren, Jack Hessel, Claire Cardie, Yejin Choi, Yuntian Deng

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics.

Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, Defne G. Ozgulbas, Natalia Vassilieva, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan

Int. J. High Perform. Comput. Appl., November, 2023

Implicit Chain of Thought Reasoning via Knowledge Distillation.

Yuntian Deng, Kiran Prasad, Roland Fernandez, Paul Smolensky, Vishrav Chaudhary, Stuart M. Shieber

CoRR, 2023

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.

Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens

CoRR, 2023

Semi-Parametric Inducing Point Networks and Neural Processes.

Richa Rastogi, Yair Schiff, Alon Hacohen, Zhaozhi Li, Ian Lee, Yuntian Deng, Mert R. Sabuncu, Volodymyr Kuleshov

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Markup-to-Image Diffusion Models with Scheduled Sampling.

Yuntian Deng, Noriyuki Kojima, Alexander M. Rush

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Tree Prompting: Efficient Task Adaptation without Fine-Tuning.

Chandan Singh, John X. Morris, Alexander M. Rush, Jianfeng Gao, Yuntian Deng

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

Fleet sizing and charger allocation in electric vehicle sharing systems.

Yuntian Deng, Abhishek Gupta, Ness B. Shroff

IFAC J. Syst. Control., 2022

Semi-Parametric Deep Neural Networks in Linear Time and Memory.

Richa Rastogi, Yuntian Deng, Ian Lee, Mert R. Sabuncu, Volodymyr Kuleshov

CoRR, 2022

Interference Constrained Beam Alignment for Time-Varying Channels via Kernelized Bandits.

Yuntian Deng, Xingyu Zhou, Arnob Ghosh, Abhishek Gupta, Ness B. Shroff

Proceedings of the 20th International Symposium on Modeling and Optimization in Mobile, 2022

Model Criticism for Long-Form Text Generation.

Yuntian Deng, Volodymyr Kuleshov, Alexander M. Rush

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Weighted Gaussian Process Bandits for Non-stationary Environments.

Yuntian Deng, Xingyu Zhou, Baekjin Kim, Ambuj Tewari, Abhishek Gupta, Ness B. Shroff

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

2021

Residual Energy-Based Models for Text.

Anton Bakhtin, Yuntian Deng, Sam Gross, Myle Ott, Marc'Aurelio Ranzato, Arthur Szlam

J. Mach. Learn. Res., 2021

Incentive Design and Profit Sharing in Multi-modal Transportation Network.

Yuntian Deng, Shiping Shao, Archak Mittal, Richard Twumasi-Boakye, James Fishelson, Abhishek Gupta, Ness B. Shroff

CoRR, 2021

Low-Rank Constraints for Fast Inference in Structured Models.

Justin T. Chiu, Yuntian Deng, Alexander M. Rush

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

Rationales for Sequential Predictions.

Keyon Vafa, Yuntian Deng, David M. Blei, Alexander M. Rush

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Sequence-to-Lattice Models for Fast Translation.

Yuntian Deng, Alexander M. Rush

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

2020

Multi-Objective Vehicle Rebalancing for Ridehailing System using a Reinforcement Learning Approach.

Yuntian Deng, Hao Chen, Shiping Shao, Jiacheng Tang, Jianzong Pi, Abhishek Gupta

CoRR, 2020

Energy-Based Models for Text.

Anton Bakhtin, Yuntian Deng, Sam Gross, Myle Ott, Marc'Aurelio Ranzato, Arthur Szlam

CoRR, 2020

Cascaded Text Generation with Markov Transformers.

Yuntian Deng, Alexander M. Rush

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

Residual Energy-Based Models for Text Generation.

Yuntian Deng, Anton Bakhtin, Myle Ott, Arthur Szlam, Marc'Aurelio Ranzato

Proceedings of the 8th International Conference on Learning Representations, 2020

Algorithm-Hardware Co-Design of Adaptive Floating-Point Encodings for Resilient Deep Learning Inference.

Thierry Tambe, En-Yu Yang, Zishen Wan, Yuntian Deng, Vijay Janapa Reddi, Alexander M. Rush, David Brooks, Gu-Yeon Wei

Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

2019

AdaptivFloat: A Floating-point based Data Type for Resilient Deep Learning Inference.

Thierry Tambe, En-Yu Yang, Zishen Wan, Yuntian Deng, Vijay Janapa Reddi, Alexander M. Rush, David Brooks, Gu-Yeon Wei

CoRR, 2019

Real or Fake? Learning to Discriminate Machine from Human Generated Text.

Anton Bakhtin, Sam Gross, Myle Ott, Yuntian Deng, Marc'Aurelio Ranzato, Arthur Szlam

CoRR, 2019

Challenges in End-to-End Neural Scientific Table Recognition.

Yuntian Deng, David S. Rosenberg, Gideon Mann

Proceedings of the 2019 International Conference on Document Analysis and Recognition, 2019

Visual Attention Model for Cross-Sectional Stock Return Prediction and End-to-End Multimodal Market Representation Learning.

Ran Zhao, Yuntian Deng, Mark Dredze, Arun Verma, David S. Rosenberg, Amanda Stent

Proceedings of the Thirty-Second International Florida Artificial Intelligence Research Society Conference, 2019

Neural Linguistic Steganography.

Zachary M. Ziegler, Yuntian Deng, Alexander M. Rush

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

Latent Alignment and Variational Attention.

Yuntian Deng, Yoon Kim, Justin T. Chiu, Demi Guo, Alexander M. Rush

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Bottom-Up Abstractive Summarization.

Sebastian Gehrmann, Yuntian Deng, Alexander M. Rush

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

OpenNMT: Neural Machine Translation Toolkit.

Guillaume Klein, Yoon Kim, Yuntian Deng, Vincent Nguyen, Jean Senellart, Alexander M. Rush

Proceedings of the 13th Conference of the Association for Machine Translation in the Americas, 2018

2017

OpenNMT: Open-source Toolkit for Neural Machine Translation.

Guillaume Klein, Yoon Kim, Yuntian Deng, Josep Maria Crego, Jean Senellart, Alexander M. Rush

CoRR, 2017

Learning Latent Space Models with Angular Constraints.

Pengtao Xie, Yuntian Deng, Yi Zhou, Abhimanu Kumar, Yaoliang Yu, James Zou, Eric P. Xing

Proceedings of the 34th International Conference on Machine Learning, 2017

Image-to-Markup Generation with Coarse-to-Fine Attention.

Yuntian Deng, Anssi Kanervisto, Jeffrey Ling, Alexander M. Rush

Proceedings of the 34th International Conference on Machine Learning, 2017

Dropout with Expectation-linear Regularization.

Xuezhe Ma, Yingkai Gao, Zhiting Hu, Yaoliang Yu, Yuntian Deng, Eduard H. Hovy

Proceedings of the 5th International Conference on Learning Representations, 2017

Neural Machine Translation with Recurrent Attention Modeling.

Zichao Yang, Zhiting Hu, Yuntian Deng, Chris Dyer, Alexander J. Smola

Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 2017

OpenNMT: Open-Source Toolkit for Neural Machine Translation.

Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, Alexander M. Rush

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

2016

What You Get Is What You See: A Visual Markup Decompiler.

Yuntian Deng, Anssi Kanervisto, Alexander M. Rush

CoRR, 2016

Learning Concept Taxonomies from Multi-modal Data.

Hao Zhang, Zhiting Hu, Yuntian Deng, Mrinmaya Sachan, Zhicheng Yan, Eric P. Xing

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

2015

Latent Variable Modeling with Diversity-Inducing Mutual Angular Regularization.

Pengtao Xie, Yuntian Deng, Eric P. Xing

CoRR, 2015

On the Generalization Error Bounds of Neural Networks under Diversity-Inducing Mutual Angular Regularization.

Pengtao Xie, Yuntian Deng, Eric P. Xing

CoRR, 2015

Creating Scalable and Interactive Web Applications Using High Performance Latent Variable Models.

Aaron Q. Li, Yuntian Deng, Kublai Jing, Joseph W. Robinson

CoRR, 2015

Diversifying Restricted Boltzmann Machine for Document Modeling.

Pengtao Xie, Yuntian Deng, Eric P. Xing

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Entity Hierarchy Embedding.

Zhiting Hu, Poyao Huang, Yuntian Deng, Yingkai Gao, Eric P. Xing

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 2015