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Dejiao Zhang
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2020 – today
- 2024
- [c22]Junlin Wang, Siddhartha Jain, Dejiao Zhang, Baishakhi Ray, Varun Kumar, Ben Athiwaratkun:
Reasoning in Token Economies: Budget-Aware Evaluation of LLM Reasoning Strategies. EMNLP 2024: 19916-19939 - [c21]Dejiao Zhang, Wasi Uddin Ahmad, Ming Tan, Hantian Ding, Ramesh Nallapati, Dan Roth, Xiaofei Ma, Bing Xiang:
Code Representation Learning at Scale. ICLR 2024 - [c20]Di Wu, Wasi Uddin Ahmad, Dejiao Zhang, Murali Krishna Ramanathan, Xiaofei Ma:
Repoformer: Selective Retrieval for Repository-Level Code Completion. ICML 2024 - [i20]Dejiao Zhang, Wasi Uddin Ahmad, Ming Tan, Hantian Ding, Ramesh Nallapati, Dan Roth, Xiaofei Ma, Bing Xiang:
Code Representation Learning At Scale. CoRR abs/2402.01935 (2024) - [i19]Di Wu, Wasi Uddin Ahmad, Dejiao Zhang, Murali Krishna Ramanathan, Xiaofei Ma:
Repoformer: Selective Retrieval for Repository-Level Code Completion. CoRR abs/2403.10059 (2024) - [i18]Junlin Wang, Siddhartha Jain, Dejiao Zhang, Baishakhi Ray, Varun Kumar, Ben Athiwaratkun:
Reasoning in Token Economies: Budget-Aware Evaluation of LLM Reasoning Strategies. CoRR abs/2406.06461 (2024) - 2023
- [c19]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:
Exploring Continual Learning for Code Generation Models. ACL (2) 2023: 782-792 - [c18]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:
ContraCLM: Contrastive Learning For Causal Language Model. ACL (1) 2023: 6436-6459 - [c17]Robert Giaquinto, Dejiao Zhang, Benjamin Kleiner, Yang Li, Ming Tan, Parminder Bhatia, Ramesh Nallapati, Xiaofei Ma:
Multitask Pretraining with Structured Knowledge for Text-to-SQL Generation. ACL (1) 2023: 11067-11083 - [i17]Prateek Yadav, Qing Sun, Hantian Ding, Xiaopeng Li, Dejiao Zhang, Ming Tan, Xiaofei Ma, Parminder Bhatia, Ramesh Nallapati, Murali Krishna Ramanathan, Mohit Bansal, Bing Xiang:
Exploring Continual Learning for Code Generation Models. CoRR abs/2307.02435 (2023) - 2022
- [c16]Dejiao Zhang, Wei Xiao, Henghui Zhu, Xiaofei Ma, Andrew O. Arnold:
Virtual Augmentation Supported Contrastive Learning of Sentence Representations. ACL (Findings) 2022: 864-876 - [c15]Zhihan Zhou, Dejiao Zhang, Wei Xiao, Nicholas Dingwall, Xiaofei Ma, Andrew O. Arnold, Bing Xiang:
Learning Dialogue Representations from Consecutive Utterances. NAACL-HLT 2022: 754-768 - [c14]Xisen Jin, Dejiao Zhang, Henghui Zhu, Wei Xiao
, Shang-Wen Li, Xiaokai Wei, Andrew O. Arnold, Xiang Ren:
Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora. NAACL-HLT 2022: 4764-4780 - [i16]Andy T. Liu, Wei Xiao, Henghui Zhu, Dejiao Zhang, Shang-Wen Li, Andrew O. Arnold:
QaNER: Prompting Question Answering Models for Few-shot Named Entity Recognition. CoRR abs/2203.01543 (2022) - [i15]Zhihan Zhou, Dejiao Zhang, Wei Xiao, Nicholas Dingwall, Xiaofei Ma, Andrew O. Arnold, Bing Xiang:
Learning Dialogue Representations from Consecutive Utterances. CoRR abs/2205.13568 (2022) - [i14]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:
ContraGen: Effective Contrastive Learning For Causal Language Model. CoRR abs/2210.01185 (2022) - 2021
- [c13]Yifan Gao, Henghui Zhu, Patrick Ng, Cícero Nogueira dos Santos, Zhiguo Wang, Feng Nan, Dejiao Zhang, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang:
Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip Prediction. ACL/IJCNLP (1) 2021: 3263-3276 - [c12]Feng Nan, Cícero Nogueira dos Santos, Henghui Zhu, Patrick Ng, Kathleen R. McKeown, Ramesh Nallapati, Dejiao Zhang, Zhiguo Wang, Andrew O. Arnold, Bing Xiang:
Improving Factual Consistency of Abstractive Summarization via Question Answering. ACL/IJCNLP (1) 2021: 6881-6894 - [c11]Feng Nan, Ramesh Nallapati, Zhiguo Wang, Cícero Nogueira dos Santos, Henghui Zhu, Dejiao Zhang, Kathy McKeown, Bing Xiang:
Entity-level Factual Consistency of Abstractive Text Summarization. EACL 2021: 2727-2733 - [c10]Dejiao Zhang, Shang-Wen Li, Wei Xiao, Henghui Zhu, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang:
Pairwise Supervised Contrastive Learning of Sentence Representations. EMNLP (1) 2021: 5786-5798 - [c9]Dejiao Zhang, Feng Nan, Xiaokai Wei, Shang-Wen Li, Henghui Zhu, Kathleen R. McKeown, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang:
Supporting Clustering with Contrastive Learning. NAACL-HLT 2021: 5419-5430 - [i13]Feng Nan, Ramesh Nallapati, Zhiguo Wang, Cícero Nogueira dos Santos, Henghui Zhu, Dejiao Zhang, Kathleen R. McKeown, Bing Xiang:
Entity-level Factual Consistency of Abstractive Text Summarization. CoRR abs/2102.09130 (2021) - [i12]Dejiao Zhang, Feng Nan, Xiaokai Wei, Shang-Wen Li, Henghui Zhu, Kathleen R. McKeown, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang:
Supporting Clustering with Contrastive Learning. CoRR abs/2103.12953 (2021) - [i11]Feng Nan, Cícero Nogueira dos Santos, Henghui Zhu, Patrick Ng, Kathleen R. McKeown, Ramesh Nallapati, Dejiao Zhang, Zhiguo Wang, Andrew O. Arnold, Bing Xiang:
Improving Factual Consistency of Abstractive Summarization via Question Answering. CoRR abs/2105.04623 (2021) - [i10]Dejiao Zhang, Shang-Wen Li, Wei Xiao, Henghui Zhu, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang:
Pairwise Supervised Contrastive Learning of Sentence Representations. CoRR abs/2109.05424 (2021) - [i9]Xiaokai Wei, Shen Wang, Dejiao Zhang, Parminder Bhatia, Andrew O. Arnold:
Knowledge Enhanced Pretrained Language Models: A Compreshensive Survey. CoRR abs/2110.08455 (2021) - [i8]Xisen Jin, Dejiao Zhang, Henghui Zhu, Wei Xiao, Shang-Wen Li, Xiaokai Wei, Andrew O. Arnold, Xiang Ren:
Lifelong Pretraining: Continually Adapting Language Models to Emerging Corpora. CoRR abs/2110.08534 (2021) - [i7]Dejiao Zhang, Wei Xiao, Henghui Zhu, Xiaofei Ma, Andrew O. Arnold:
Virtual Augmentation Supported Contrastive Learning of Sentence Representations. CoRR abs/2110.08552 (2021) - 2020
- [c8]Dejiao Zhang, Ramesh Nallapati, Henghui Zhu, Feng Nan, Cícero Nogueira dos Santos, Kathleen R. McKeown, Bing Xiang:
Unsupervised Domain Adaptation for Cross-lingual Text Labeling. EMNLP (Findings) 2020: 3527-3536 - [i6]Yifan Gao, Henghui Zhu, Patrick Ng, Cícero Nogueira dos Santos, Zhiguo Wang, Feng Nan, Dejiao Zhang, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang:
Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip Prediction. CoRR abs/2011.13137 (2020)
2010 – 2019
- 2018
- [c7]Dejiao Zhang, Haozhu Wang, Mário A. T. Figueiredo, Laura Balzano:
Learning to Share: simultaneous parameter tying and Sparsification in Deep Learning. ICLR (Poster) 2018 - [c6]Dejiao Zhang, Julian Katz-Samuels, Mário A. T. Figueiredo, Laura Balzano
Simultaneous Sparsity and Parameter Tying for Deep Learning Using Ordered Weighted ℓ1 Regularization. SSP 2018: 65-69 - [c5]Greg Ongie
Online Estimation of Coherent Subspaces with Adaptive Sampling. SSP 2018: 841-845 - 2017
- [c4]Greg Ongie
Enhanced online subspace estimation via adaptive sensing. ACSSC 2017: 993-997 - [c3]Dejiao Zhang, Laura Balzano
Matched subspace detection using compressively sampled data. ICASSP 2017: 4601-4605 - [i5]John Lipor, David Hong, Dejiao Zhang, Laura Balzano:
Subspace Clustering using Ensembles of $K$-Subspaces. CoRR abs/1709.04744 (2017) - [i4]Dejiao Zhang, Yifan Sun, Brian Eriksson, Laura Balzano:
Deep Unsupervised Clustering Using Mixture of Autoencoders. CoRR abs/1712.07788 (2017) - 2016
- [c2]Dejiao Zhang, Laura Balzano:
Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation. AISTATS 2016: 1460-1468 - [i3]Dejiao Zhang, Laura Balzano:
Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation From Undersampled Data. CoRR abs/1610.00199 (2016) - 2015
- [i2]Dejiao Zhang, Laura Balzano:
Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation. CoRR abs/1506.07405 (2015) - 2014
- [j1]Jun He
Iterative Grassmannian optimization for robust image alignment. Image Vis. Comput. 32(10): 800-813 (2014) - 2013
- [c1]Jun He
Iterative online subspace learning for robust image alignment. FG 2013: 1-8 - [i1]Jun He, Dejiao Zhang, Laura Balzano, Tao Tao:
Iterative Grassmannian Optimization for Robust Image Alignment. CoRR abs/1306.0404 (2013)
Coauthor Index
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last updated on 2024-11-15 19:33 CET by the dblp team
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