Entity Hierarchy Embedding. - Zhiting Hu; Poyao Huang 001; Yuntian Deng; Yingkai Gao; Eric P. Xing (ACL (1), 2015)

Diversifying Restricted Boltzmann Machine for Document Modeling. - Pengtao Xie; Yuntian Deng; Eric P. Xing (KDD, 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)

On the Generalization Error Bounds of Neural Networks under Diversity-Inducing Mutual Angular Regularization. - Pengtao Xie; Yuntian Deng; Eric P. Xing (CoRR, 2015)

Latent Variable Modeling with Diversity-Inducing Mutual Angular Regularization. - Pengtao Xie; Yuntian Deng; Eric P. Xing (CoRR, 2015)

Learning Concept Taxonomies from Multi-modal Data. - Hao Zhang 025; Zhiting Hu; Yuntian Deng; Mrinmaya Sachan; Zhicheng Yan 001; Eric P. Xing (ACL (1), 2016)

What You Get Is What You See: A Visual Markup Decompiler. - Yuntian Deng; Anssi Kanervisto; Alexander M. Rush (CoRR, 2016)

OpenNMT: Open-Source Toolkit for Neural Machine Translation. - Guillaume Klein; Yoon Kim; Yuntian Deng; Jean Senellart; Alexander M. Rush (ACL (System Demonstrations), 2017)

Neural Machine Translation with Recurrent Attention Modeling. - Zichao Yang; Zhiting Hu; Yuntian Deng; Chris Dyer; Alexander J. Smola (EACL (2), 2017)

Dropout with Expectation-linear Regularization. - Xuezhe Ma; Yingkai Gao; Zhiting Hu; Yaoliang Yu; Yuntian Deng; Eduard H. Hovy (ICLR (Poster), 2017)

Image-to-Markup Generation with Coarse-to-Fine Attention. - Yuntian Deng; Anssi Kanervisto; Jeffrey Ling; Alexander M. Rush (ICML, 2017)

Learning Latent Space Models with Angular Constraints. - Pengtao Xie; Yuntian Deng; Yi Zhou 017; Abhimanu Kumar; Yaoliang Yu; James Zou 001; Eric P. Xing (ICML, 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)

OpenNMT: Neural Machine Translation Toolkit. - Guillaume Klein; Yoon Kim; Yuntian Deng; Vincent Nguyen; Jean Senellart; Alexander M. Rush (AMTA (1), 2018)

Bottom-Up Abstractive Summarization. - Sebastian Gehrmann; Yuntian Deng; Alexander M. Rush (EMNLP, 2018)

Latent Alignment and Variational Attention. - Yuntian Deng; Yoon Kim; Justin T. Chiu; Demi Guo; Alexander M. Rush (NeurIPS, 2018)

Neural Linguistic Steganography. - Zachary M. Ziegler; Yuntian Deng; Alexander M. Rush (EMNLP/IJCNLP (1), 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 (FLAIRS, 2019)

Challenges in End-to-End Neural Scientific Table Recognition. - Yuntian Deng; David S. Rosenberg; Gideon Mann (ICDAR, 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)

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 001; Gu-Yeon Wei (CoRR, 2019)

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 001; Gu-Yeon Wei (DAC, 2020)

Residual Energy-Based Models for Text Generation. - Yuntian Deng; Anton Bakhtin; Myle Ott; Arthur Szlam; Marc'Aurelio Ranzato (ICLR, 2020)

Cascaded Text Generation with Markov Transformers. - Yuntian Deng; Alexander M. Rush (NeurIPS, 2020)

Energy-Based Models for Text. - Anton Bakhtin; Yuntian Deng; Sam Gross; Myle Ott; Marc'Aurelio Ranzato; Arthur Szlam (CoRR, 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 002 (CoRR, 2020)

Sequence-to-Lattice Models for Fast Translation. - Yuntian Deng; Alexander M. Rush (EMNLP (Findings), 2021)

Rationales for Sequential Predictions. - Keyon Vafa; Yuntian Deng; David M. Blei; Alexander M. Rush (EMNLP (1), 2021)

Low-Rank Constraints for Fast Inference in Structured Models. - Justin T. Chiu; Yuntian Deng; Alexander M. Rush (NeurIPS, 2021)

Incentive Design and Profit Sharing in Multi-modal Transportation Network. - Yuntian Deng; Shiping Shao; Archak Mittal; Richard Twumasi-Boakye; James Fishelson; Abhishek Gupta 002; Ness B. Shroff (CoRR, 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)

Weighted Gaussian Process Bandits for Non-stationary Environments. - Yuntian Deng; Xingyu Zhou 001; Baekjin Kim; Ambuj Tewari; Abhishek Gupta 002; Ness B. Shroff (AISTATS, 2022)

Model Criticism for Long-Form Text Generation. - Yuntian Deng; Volodymyr Kuleshov; Alexander M. Rush (EMNLP, 2022)

Interference Constrained Beam Alignment for Time-Varying Channels via Kernelized Bandits. - Yuntian Deng; Xingyu Zhou 001; Arnob Ghosh; Abhishek Gupta 002; Ness B. Shroff (WiOpt, 2022)

Semi-Parametric Deep Neural Networks in Linear Time and Memory. - Richa Rastogi; Yuntian Deng; Ian Lee; Mert R. Sabuncu; Volodymyr Kuleshov (CoRR, 2022)

Fleet sizing and charger allocation in electric vehicle sharing systems. - Yuntian Deng; Abhishek Gupta 002; Ness B. Shroff (IFAC J. Syst. Control., 2022)

Tree Prompting: Efficient Task Adaptation without Fine-Tuning. - Chandan Singh; John X. Morris; Alexander M. Rush; Jianfeng Gao 001; Yuntian Deng (EMNLP, 2023)

Markup-to-Image Diffusion Models with Scheduled Sampling. - Yuntian Deng; Noriyuki Kojima; Alexander M. Rush (ICLR, 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 (ICLR, 2023)

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. - Shuaiwen Leon Song; Bonnie Kruft; Minjia Zhang; Conglong Li; Shiyang Chen 004; Chengming Zhang 006; Masahiro Tanaka; Xiaoxia Wu; Jeff Rasley; Ammar Ahmad Awan; Connor Holmes; Martin Cai; et al. (CoRR, 2023)

Implicit Chain of Thought Reasoning via Knowledge Distillation. - Yuntian Deng; Kiran Prasad; Roland Fernandez; Paul Smolensky; Vishrav Chaudhary; Stuart M. Shieber (CoRR, 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; et al. (Int. J. High Perform. Comput. Appl., 2023)

WildChat: 1M ChatGPT Interaction Logs in the Wild. - Wenting Zhao; Xiang Ren 001; Jack Hessel; Claire Cardie; Yejin Choi 001; Yuntian Deng (ICLR, 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 001 (NeurIPS, 2024)

From Explicit CoT to Implicit CoT: Learning to Internalize CoT Step by Step. - Yuntian Deng; Yejin Choi 001; Stuart M. Shieber (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 001; Yejin Choi 001 (CoRR, 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 001; Claire Cardie; Yuntian Deng; Yejin Choi 001 (CoRR, 2024)

WildVis: Open Source Visualizer for Million-Scale Chat Logs in the Wild. - Yuntian Deng; Wenting Zhao; Jack Hessel; Xiang Ren 001; Claire Cardie; Yejin Choi 001 (CoRR, 2024)

WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild. - Bill Yuchen Lin; Yuntian Deng; Khyathi Raghavi Chandu; Abhilasha Ravichander; Valentina Pyatkin; Nouha Dziri; Ronan Le Bras 001; Yejin Choi 001 (ICLR, 2025)

MixEval-X: Any-to-any Evaluations from Real-world Data Mixture. - Jinjie Ni; Yifan Song; Deepanway Ghosal; Bo Li; David Junhao Zhang; Xiang Yue; Fuzhao Xue; Yuntian Deng; Zian Zheng 001; Kaichen Zhang; Mahir Shah; Kabir Jain; et al. (ICLR, 2025)

Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing. - Zhangchen Xu; Fengqing Jiang; Luyao Niu; Yuntian Deng; Radha Poovendran; Yejin Choi 001; Bill Yuchen Lin (ICLR, 2025)

Mix-of-Language-Experts Architecture for Multilingual Programming. - Yifan Zong; Yuntian Deng; Pengyu Nie 001 (LLM4Code@ICSE, 2025)

The Leaderboard Illusion. - Shivalika Singh; Yiyang Nan; Alex Wang; Daniel D'souza; Sayash Kapoor; Ahmet Üstün; Sanmi Koyejo; Yuntian Deng; Shayne Longpre; Noah Smith; Beyza Ermis; Marzieh Fadaee; et al. (CoRR, 2025)

Learn to Reason Efficiently with Adaptive Length-based Reward Shaping. - Wei Liu 131; Ruochen Zhou; Yiyun Deng; Yuzhen Huang; Junteng Liu; Yuntian Deng; Yizhe Zhang; Junxian He (CoRR, 2025)

From Chat Logs to Collective Insights: Aggregative Question Answering. - Wentao Zhang; Woojeong Kim; Yuntian Deng (CoRR, 2025)

NeuralOS: Towards Simulating Operating Systems via Neural Generative Models. - Luke Rivard; Sun Sun; Hongyu Guo; Wenhu Chen; Yuntian Deng (CoRR, 2025)