Zhengbao Jiang

According to our database, Zhengbao Jiang authored at least 32 papers between 2016 and 2024.

Collaborative distances:

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

2024

Beyond Memorization: The Challenge of Random Memory Access in Language Models.

Tongyao Zhu, Qian Liu, Liang Pang, Zhengbao Jiang, Min-Yen Kan, Min Lin

CoRR, 2024

Instruction-tuned Language Models are Better Knowledge Learners.

Zhengbao Jiang, Zhiqing Sun, Weijia Shi, Pedro Rodriguez, Chunting Zhou, Graham Neubig, Xi Victoria Lin, Wen-tau Yih, Srinivasan Iyer

CoRR, 2024

2023

Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing.

Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, Graham Neubig

ACM Comput. Surv., 2023

Learning to Filter Context for Retrieval-Augmented Generation.

Zhiruo Wang, Jun Araki, Zhengbao Jiang, Md. Rizwan Parvez, Graham Neubig

CoRR, 2023

From Zero to Hero: Examining the Power of Symbolic Tasks in Instruction Tuning.

Qian Liu, Fan Zhou, Zhengbao Jiang, Longxu Dou, Min Lin

CoRR, 2023

GPTScore: Evaluate as You Desire.

Jinlan Fu, See-Kiong Ng, Zhengbao Jiang, Pengfei Liu

CoRR, 2023

DocPrompting: Generating Code by Retrieving the Docs.

Shuyan Zhou, Uri Alon, Frank F. Xu, Zhengbao Jiang, Graham Neubig

Proceedings of the Eleventh International Conference on Learning Representations, 2023

PEER: A Collaborative Language Model.

Timo Schick, Jane A. Yu, Zhengbao Jiang, Fabio Petroni, Patrick S. H. Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, Sebastian Riedel

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Active Retrieval Augmented Generation.

Zhengbao Jiang, Frank F. Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, Graham Neubig

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

2022

EditEval: An Instruction-Based Benchmark for Text Improvements.

Jane Dwivedi-Yu, Timo Schick, Zhengbao Jiang, Maria Lomeli, Patrick S. H. Lewis, Gautier Izacard, Edouard Grave, Sebastian Riedel, Fabio Petroni

CoRR, 2022

DocCoder: Generating Code by Retrieving and Reading Docs.

Shuyan Zhou, Uri Alon, Frank F. Xu, Zhengbao Jiang, Graham Neubig

CoRR, 2022

Table Retrieval May Not Necessitate Table-specific Model Design.

Zhiruo Wang, Zhengbao Jiang, Eric Nyberg, Graham Neubig

CoRR, 2022

OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering.

Zhengbao Jiang, Yi Mao, Pengcheng He, Graham Neubig, Weizhu Chen

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

SPE: Symmetrical Prompt Enhancement for Fact Probing.

Yiyuan Li, Tong Che, Yezhen Wang, Zhengbao Jiang, Caiming Xiong, Snigdha Chaturvedi

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

Retrieval as Attention: End-to-end Learning of Retrieval and Reading within a Single Transformer.

Zhengbao Jiang, Luyu Gao, Zhiruo Wang, Jun Araki, Haibo Ding, Jamie Callan, Graham Neubig

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

Understanding and Improving Zero-shot Multi-hop Reasoning in Generative Question Answering.

Zhengbao Jiang, Jun Araki, Haibo Ding, Graham Neubig

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021

How Can We Know <i>When</i> Language Models Know? On the Calibration of Language Models for Question Answering.

Zhengbao Jiang, Jun Araki, Haibo Ding, Graham Neubig

Trans. Assoc. Comput. Linguistics, 2021

GSum: A General Framework for Guided Neural Abstractive Summarization.

Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi, Zhengbao Jiang, Graham Neubig

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

CoRI: Collective Relation Integration with Data Augmentation for Open Information Extraction.

Zhengbao Jiang, Jialong Han, Bunyamin Sisman, Xin Luna Dong

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

2020

How Can We Know What Language Models Know.

Zhengbao Jiang, Frank F. Xu, Jun Araki, Graham Neubig

Trans. Assoc. Comput. Linguistics, 2020

How Can We Know When Language Models Know?

Zhengbao Jiang, Jun Araki, Haibo Ding, Graham Neubig

CoRR, 2020

Graph-Revised Convolutional Network.

Donghan Yu, Ruohong Zhang, Zhengbao Jiang, Yuexin Wu, Yiming Yang

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

X-FACTR: Multilingual Factual Knowledge Retrieval from Pretrained Language Models.

Zhengbao Jiang, Antonios Anastasopoulos, Jun Araki, Haibo Ding, Graham Neubig

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Learning Relation Entailment with Structured and Textual Information.

Zhengbao Jiang, Jun Araki, Donghan Yu, Ruohong Zhang, Wei Xu, Yiming Yang, Graham Neubig

Proceedings of the Conference on Automated Knowledge Base Construction, 2020

Incorporating External Knowledge through Pre-training for Natural Language to Code Generation.

Frank F. Xu, Zhengbao Jiang, Pengcheng Yin, Bogdan Vasilescu, Graham Neubig

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Generalizing Natural Language Analysis through Span-relation Representations.

Zhengbao Jiang, Wei Xu, Jun Araki, Graham Neubig

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Improving Open Information Extraction via Iterative Rank-Aware Learning.

Zhengbao Jiang, Pengcheng Yin, Graham Neubig

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Supervised Search Result Diversification via Subtopic Attention.

Zhengbao Jiang, Zhicheng Dou, Wayne Xin Zhao, Jian-Yun Nie, Ming Yue, Ji-Rong Wen

IEEE Trans. Knowl. Data Eng., 2018

Personalizing Search Results Using Hierarchical RNN with Query-aware Attention.

Songwei Ge, Zhicheng Dou, Zhengbao Jiang, Jian-Yun Nie, Ji-Rong Wen

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017

Generating Query Facets Using Knowledge Bases.

Zhengbao Jiang, Zhicheng Dou, Ji-Rong Wen

IEEE Trans. Knowl. Data Eng., 2017

Learning to Diversify Search Results via Subtopic Attention.

Zhengbao Jiang, Ji-Rong Wen, Zhicheng Dou, Wayne Xin Zhao, Jian-Yun Nie, Ming Yue

Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017

2016

Automatically Mining Facets for Queries from Their Search Results.

Zhicheng Dou, Zhengbao Jiang, Sha Hu, Ji-Rong Wen, Ruihua Song

IEEE Trans. Knowl. Data Eng., 2016