Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation. - Adam Poliak; Aparajita Haldar; Rachel Rudinger; J. Edward Hu; Ellie Pavlick; Aaron Steven White; Benjamin Van Durme (BlackboxNLP@EMNLP, 2018)

Towards a Unified Natural Language Inference Framework to Evaluate Sentence Representations. - Adam Poliak; Aparajita Haldar; Rachel Rudinger; J. Edward Hu; Ellie Pavlick; Aaron Steven White; Benjamin Van Durme (CoRR, 2018)

PARABANK: Monolingual Bitext Generation and Sentential Paraphrasing via Lexically-Constrained Neural Machine Translation. - J. Edward Hu; Rachel Rudinger; Matt Post; Benjamin Van Durme (AAAI, 2019)

Large-Scale, Diverse, Paraphrastic Bitexts via Sampling and Clustering. - J. Edward Hu; Abhinav Singh; Nils Holzenberger; Matt Post; Benjamin Van Durme (CoNLL, 2019)

Improved Lexically Constrained Decoding for Translation and Monolingual Rewriting. - J. Edward Hu; Huda Khayrallah; Ryan Culkin; Patrick Xia 002; Tongfei Chen; Matt Post; Benjamin Van Durme (NAACL-HLT (1), 2019)

NIST TAC SM-KBP 2019 System Description: JHU/UR Framework. - Yunmo Chen; Seth Ebner; Tongfei Chen; Patrick Xia 002; Elias Stengel-Eskin; Tzu-Ray Su; J. Edward Hu; Nils Holzenberger; Ryan Culkin; Craig Harman; Max Thomas; Thomas Lippincott; et al. (TAC, 2019)

Randomized Smoothing of All Shapes and Sizes. - Greg Yang; Tony Duan; J. Edward Hu; Hadi Salman; Ilya P. Razenshteyn; Jerry Li 001 (ICML, 2020)

Guided Generation of Cause and Effect. - Zhongyang Li; Xiao Ding; Ting Liu 001; J. Edward Hu; Benjamin Van Durme (IJCAI, 2020)

Improved Image Wasserstein Attacks and Defenses. - J. Edward Hu; Adith Swaminathan; Hadi Salman; Greg Yang (CoRR, 2020)

Feature Learning in Infinite-Width Neural Networks. - Greg Yang; J. Edward Hu (CoRR, 2020)

Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks. - Greg Yang; Edward J. Hu (ICML, 2021)

Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer. - Ge Yang; Edward J. Hu; Igor Babuschkin; Szymon Sidor; Xiaodong Liu 003; David Farhi; Nick Ryder; Jakub Pachocki; Weizhu Chen; Jianfeng Gao 001 (NeurIPS, 2021)

LoRA: Low-Rank Adaptation of Large Language Models. - Edward J. Hu; Yelong Shen; Phillip Wallis; Zeyuan Allen-Zhu; Yuanzhi Li; Shean Wang; Weizhu Chen (CoRR, 2021)

Iterative Paraphrastic Augmentation with Discriminative Span Alignment. - Ryan Culkin; J. Edward Hu; Elias Stengel-Eskin; Guanghui Qin; Benjamin Van Durme (Trans. Assoc. Comput. Linguistics, 2021)

LoRA: Low-Rank Adaptation of Large Language Models. - Edward J. Hu; Yelong Shen; Phillip Wallis; Zeyuan Allen-Zhu; Yuanzhi Li; Shean Wang; Lu Wang; Weizhu Chen (ICLR, 2022)

Efficient Computation of Deep Nonlinear Infinite-Width Neural Networks that Learn Features. - Greg Yang; Michael Santacroce; Edward J. Hu (ICLR, 2022)

Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer. - Greg Yang; Edward J. Hu; Igor Babuschkin; Szymon Sidor; Xiaodong Liu 003; David Farhi; Nick Ryder; Jakub Pachocki; Weizhu Chen; Jianfeng Gao 001 (CoRR, 2022)

GFlowNets and variational inference. - Nikolay Malkin; Salem Lahlou; Tristan Deleu; Xu Ji; Edward J. Hu; Katie Everett; Dinghuai Zhang; Yoshua Bengio (ICLR, 2023)

GFlowNet-EM for Learning Compositional Latent Variable Models. - Edward J. Hu; Nikolay Malkin; Moksh Jain; Katie E. Everett; Alexandros Graikos; Yoshua Bengio (ICML, 2023)

Differentiable Tree Operations Promote Compositional Generalization. - Paul Soulos; Edward J. Hu; Kate McCurdy; Yunmo Chen; Roland Fernandez; Paul Smolensky; Jianfeng Gao 001 (ICML, 2023)

GFlowNet Foundations. - Yoshua Bengio; Salem Lahlou; Tristan Deleu; Edward J. Hu; Mo Tiwari; Emmanuel Bengio (J. Mach. Learn. Res., 2023)

Amortizing intractable inference in large language models. - Edward J. Hu; Moksh Jain; Eric Elmoznino; Younesse Kaddar; Guillaume Lajoie; Yoshua Bengio; Nikolay Malkin (ICLR, 2024)