Dejiao Zhang

According to our database, Dejiao Zhang authored at least 29 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Repoformer: Selective Retrieval for Repository-Level Code Completion.

Di Wu, Wasi Uddin Ahmad, Dejiao Zhang, Murali Krishna Ramanathan, Xiaofei Ma

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Code Representation Learning at Scale.

Dejiao Zhang, Wasi Uddin Ahmad, Ming Tan, Hantian Ding, Ramesh Nallapati, Dan Roth, Xiaofei Ma, Bing Xiang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Reasoning in Token Economies: Budget-Aware Evaluation of LLM Reasoning Strategies.

Junlin Wang, Siddhartha Jain, Dejiao Zhang, Baishakhi Ray, Varun Kumar, Ben Athiwaratkun

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Exploring Continual Learning for Code Generation Models.

Prateek Yadav, Qing Sun, Hantian Ding, Xiaopeng Li, Dejiao Zhang, Ming Tan, Parminder Bhatia, Xiaofei Ma, Ramesh Nallapati, Murali Krishna Ramanathan, Mohit Bansal, Bing Xiang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

ContraCLM: Contrastive Learning For Causal Language Model.

Nihal Jain, Dejiao Zhang, Wasi Uddin Ahmad, Zijian Wang, Feng Nan, Xiaopeng Li, Ming Tan, Ramesh Nallapati, Baishakhi Ray, Parminder Bhatia, Xiaofei Ma, Bing Xiang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Multitask Pretraining with Structured Knowledge for Text-to-SQL Generation.

Robert Giaquinto, Dejiao Zhang, Benjamin Kleiner, Yang Li, Ming Tan, Parminder Bhatia, Ramesh Nallapati, Xiaofei Ma

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

ContraGen: Effective Contrastive Learning For Causal Language Model.

Nihal Jain, Dejiao Zhang, Wasi Uddin Ahmad, Zijian Wang, Feng Nan, Xiaopeng Li, Ming Tan, Ramesh Nallapati, Baishakhi Ray, Parminder Bhatia, Xiaofei Ma, Bing Xiang

CoRR, 2022

QaNER: Prompting Question Answering Models for Few-shot Named Entity Recognition.

Andy T. Liu, Wei Xiao, Henghui Zhu, Dejiao Zhang, Shang-Wen Li, Andrew O. Arnold

CoRR, 2022

Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora.

Xisen Jin, Dejiao Zhang, Henghui Zhu, Wei Xiao, Shang-Wen Li, Xiaokai Wei, Andrew O. Arnold, Xiang Ren

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Learning Dialogue Representations from Consecutive Utterances.

Zhihan Zhou, Dejiao Zhang, Wei Xiao, Nicholas Dingwall, Xiaofei Ma, Andrew O. Arnold, Bing Xiang

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Virtual Augmentation Supported Contrastive Learning of Sentence Representations.

Dejiao Zhang, Wei Xiao, Henghui Zhu, Xiaofei Ma, Andrew O. Arnold

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

Knowledge Enhanced Pretrained Language Models: A Compreshensive Survey.

Xiaokai Wei, Shen Wang, Dejiao Zhang, Parminder Bhatia, Andrew O. Arnold

CoRR, 2021

Supporting Clustering with Contrastive Learning.

Dejiao Zhang, Feng Nan, Xiaokai Wei, Shang-Wen Li, Henghui Zhu, Kathleen R. McKeown, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Pairwise Supervised Contrastive Learning of Sentence Representations.

Dejiao Zhang, Shang-Wen Li, Wei Xiao, Henghui Zhu, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang

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

Entity-level Factual Consistency of Abstractive Text Summarization.

Feng Nan, Ramesh Nallapati, Zhiguo Wang, Cícero Nogueira dos Santos, Henghui Zhu, Dejiao Zhang, Kathy McKeown, Bing Xiang

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

Improving Factual Consistency of Abstractive Summarization via Question Answering.

Feng Nan, Cícero Nogueira dos Santos, Henghui Zhu, Patrick Ng, Kathleen R. McKeown, Ramesh Nallapati, Dejiao Zhang, Zhiguo Wang, Andrew O. Arnold, Bing Xiang

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip Prediction.

Yifan Gao, Henghui Zhu, Patrick Ng, Cícero Nogueira dos Santos, Zhiguo Wang, Feng Nan, Dejiao Zhang, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Unsupervised Domain Adaptation for Cross-lingual Text Labeling.

Dejiao Zhang, Ramesh Nallapati, Henghui Zhu, Feng Nan, Cícero Nogueira dos Santos, Kathleen R. McKeown, Bing Xiang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

2018

Simultaneous Sparsity and Parameter Tying for Deep Learning Using Ordered Weighted ℓ1 Regularization.

Dejiao Zhang, Julian Katz-Samuels, Mário A. T. Figueiredo, Laura Balzano

Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

Online Estimation of Coherent Subspaces with Adaptive Sampling.

Greg Ongie, David Hong, Dejiao Zhang, Laura Balzano

Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

Learning to Share: simultaneous parameter tying and Sparsification in Deep Learning.

Dejiao Zhang, Haozhu Wang, Mário A. T. Figueiredo, Laura Balzano

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Deep Unsupervised Clustering Using Mixture of Autoencoders.

Dejiao Zhang, Yifan Sun, Brian Eriksson, Laura Balzano

CoRR, 2017

Subspace Clustering using Ensembles of $K$-Subspaces.

John Lipor, David Hong, Dejiao Zhang, Laura Balzano

CoRR, 2017

Matched subspace detection using compressively sampled data.

Dejiao Zhang, Laura Balzano

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Enhanced online subspace estimation via adaptive sensing.

Greg Ongie, David Hong, Dejiao Zhang, Laura Balzano

Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016

Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation From Undersampled Data.

Dejiao Zhang, Laura Balzano

CoRR, 2016

Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation.

Dejiao Zhang, Laura Balzano

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2014

Iterative Grassmannian optimization for robust image alignment.

Jun He, Dejiao Zhang, Laura Balzano, Tao Tao

Image Vis. Comput., 2014

2013

Iterative online subspace learning for robust image alignment.

Jun He, Dejiao Zhang, Laura Balzano, Tao Tao

Proceedings of the 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, 2013