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2020 – today
- 2024
[c20]Tongyao Zhu, Qian Liu, Liang Pang, Zhengbao Jiang, Min-Yen Kan, Min Lin:
Beyond Memorization: The Challenge of Random Memory Access in Language Models. ACL (1) 2024: 3373-3388- [c19]Zhengbao Jiang, Zhiqing Sun, Weijia Shi, Pedro Rodríguez, Chunting Zhou, Graham Neubig, Xi Victoria Lin, Wen-tau Yih, Srini Iyer:
Instruction-tuned Language Models are Better Knowledge Learners. ACL (1) 2024: 5421-5434 - [c18]Jinlan Fu, See-Kiong Ng, Zhengbao Jiang, Pengfei Liu:
GPTScore: Evaluate as You Desire. NAACL-HLT 2024: 6556-6576 - [i25]Zhengbao Jiang, Zhiqing Sun, Weijia Shi, Pedro Rodriguez, Chunting Zhou, Graham Neubig, Xi Victoria Lin, Wen-tau Yih, Srinivasan Iyer:
Instruction-tuned Language Models are Better Knowledge Learners. CoRR abs/2402.12847 (2024) - [i24]Tongyao Zhu, Qian Liu, Liang Pang, Zhengbao Jiang, Min-Yen Kan, Min Lin:
Beyond Memorization: The Challenge of Random Memory Access in Language Models. CoRR abs/2403.07805 (2024) - 2023
- [j6]Pengfei Liu
, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, Graham Neubig:
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing. ACM Comput. Surv. 55(9): 195:1-195:35 (2023) - [c17]Zhengbao Jiang, Frank F. Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, Graham Neubig:
Active Retrieval Augmented Generation. EMNLP 2023: 7969-7992 - [c16]Timo Schick, Jane A. Yu, Zhengbao Jiang, Fabio Petroni, Patrick Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, Sebastian Riedel:
PEER: A Collaborative Language Model. ICLR 2023 - [c15]Shuyan Zhou, Uri Alon, Frank F. Xu, Zhengbao Jiang, Graham Neubig:
DocPrompting: Generating Code by Retrieving the Docs. ICLR 2023 - [i23]Jinlan Fu, See-Kiong Ng, Zhengbao Jiang, Pengfei Liu:
GPTScore: Evaluate as You Desire. CoRR abs/2302.04166 (2023) - [i22]Qian Liu, Fan Zhou, Zhengbao Jiang, Longxu Dou, Min Lin:
From Zero to Hero: Examining the Power of Symbolic Tasks in Instruction Tuning. CoRR abs/2304.07995 (2023) - [i21]Zhengbao Jiang, Frank F. Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, Graham Neubig:
Active Retrieval Augmented Generation. CoRR abs/2305.06983 (2023) - [i20]Zhiruo Wang, Jun Araki, Zhengbao Jiang, Md. Rizwan Parvez, Graham Neubig:
Learning to Filter Context for Retrieval-Augmented Generation. CoRR abs/2311.08377 (2023) - 2022
- [c14]Zhengbao Jiang, Jun Araki, Haibo Ding, Graham Neubig:
Understanding and Improving Zero-shot Multi-hop Reasoning in Generative Question Answering. COLING 2022: 1765-1775 - [c13]Zhengbao Jiang, Luyu Gao, Zhiruo Wang, Jun Araki, Haibo Ding, Jamie Callan, Graham Neubig:
Retrieval as Attention: End-to-end Learning of Retrieval and Reading within a Single Transformer. EMNLP 2022: 2336-2349 - [c12]Yiyuan Li, Tong Che, Yezhen Wang, Zhengbao Jiang, Caiming Xiong, Snigdha Chaturvedi:
SPE: Symmetrical Prompt Enhancement for Fact Probing. EMNLP 2022: 11689-11698 - [c11]Zhengbao Jiang, Yi Mao, Pengcheng He, Graham Neubig, Weizhu Chen:
OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering. NAACL-HLT 2022: 932-942 - [i19]Zhiruo Wang, Zhengbao Jiang, Eric Nyberg, Graham Neubig:
Table Retrieval May Not Necessitate Table-specific Model Design. CoRR abs/2205.09843 (2022) - [i18]Zhengbao Jiang, Yi Mao, Pengcheng He, Graham Neubig, Weizhu Chen:
OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering. CoRR abs/2207.03637 (2022) - [i17]Shuyan Zhou, Uri Alon, Frank F. Xu, Zhengbao Jiang, Graham Neubig:
DocCoder: Generating Code by Retrieving and Reading Docs. CoRR abs/2207.05987 (2022) - [i16]Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, Fabio Petroni, Patrick Lewis, Gautier Izacard, Qingfei You, Christoforos Nalmpantis, Edouard Grave, Sebastian Riedel:
PEER: A Collaborative Language Model. CoRR abs/2208.11663 (2022) - [i15]Jane Dwivedi-Yu, Timo Schick, Zhengbao Jiang, Maria Lomeli, Patrick Lewis, Gautier Izacard, Edouard Grave, Sebastian Riedel, Fabio Petroni:
EditEval: An Instruction-Based Benchmark for Text Improvements. CoRR abs/2209.13331 (2022) - [i14]Zhengbao Jiang, Jun Araki, Haibo Ding, Graham Neubig:
Understanding and Improving Zero-shot Multi-hop Reasoning in Generative Question Answering. CoRR abs/2210.04234 (2022) - [i13]Yiyuan Li, Tong Che, Yezhen Wang, Zhengbao Jiang, Caiming Xiong, Snigdha Chaturvedi:
SPE: Symmetrical Prompt Enhancement for Fact Probing. CoRR abs/2211.07078 (2022) - [i12]Zhengbao Jiang, Luyu Gao, Jun Araki, Haibo Ding, Zhiruo Wang, Jamie Callan, Graham Neubig:
Retrieval as Attention: End-to-end Learning of Retrieval and Reading within a Single Transformer. CoRR abs/2212.02027 (2022) - 2021
- [j5]Zhengbao Jiang, Jun Araki, Haibo Ding, Graham Neubig:
How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answering. Trans. Assoc. Comput. Linguistics 9: 962-977 (2021) - [c10]Zhengbao Jiang, Jialong Han, Bunyamin Sisman, Xin Luna Dong:
CoRI: Collective Relation Integration with Data Augmentation for Open Information Extraction. ACL/IJCNLP (1) 2021: 4706-4716 - [c9]Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi, Zhengbao Jiang, Graham Neubig:
GSum: A General Framework for Guided Neural Abstractive Summarization. NAACL-HLT 2021: 4830-4842 - [i11]Zhengbao Jiang, Jialong Han, Bunyamin Sisman, Xin Luna Dong:
CoRI: Collective Relation Integration with Data Augmentation for Open Information Extraction. CoRR abs/2106.00793 (2021) - [i10]Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, Graham Neubig:
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing. CoRR abs/2107.13586 (2021) - 2020
- [j4]Zhengbao Jiang, Frank F. Xu, Jun Araki, Graham Neubig:
How Can We Know What Language Models Know. Trans. Assoc. Comput. Linguistics 8: 423-438 (2020) - [c8]Zhengbao Jiang, Wei Xu, Jun Araki, Graham Neubig:
Generalizing Natural Language Analysis through Span-relation Representations. ACL 2020: 2120-2133 - [c7]Frank F. Xu, Zhengbao Jiang, Pengcheng Yin, Bogdan Vasilescu, Graham Neubig:
Incorporating External Knowledge through Pre-training for Natural Language to Code Generation. ACL 2020: 6045-6052 - [c6]Zhengbao Jiang, Jun Araki, Donghan Yu, Ruohong Zhang, Wei Xu, Yiming Yang, Graham Neubig:
Learning Relation Entailment with Structured and Textual Information. AKBC 2020 - [c5]Zhengbao Jiang, Antonios Anastasopoulos, Jun Araki, Haibo Ding, Graham Neubig:
X-FACTR: Multilingual Factual Knowledge Retrieval from Pretrained Language Models. EMNLP (1) 2020: 5943-5959 - [c4]Donghan Yu, Ruohong Zhang, Zhengbao Jiang, Yuexin Wu, Yiming Yang:
Graph-Revised Convolutional Network. ECML/PKDD (3) 2020: 378-393 - [i9]Frank F. Xu, Zhengbao Jiang, Pengcheng Yin, Bogdan Vasilescu, Graham Neubig:
Incorporating External Knowledge through Pre-training for Natural Language to Code Generation. CoRR abs/2004.09015 (2020) - [i8]Zhengbao Jiang, Antonios Anastasopoulos, Jun Araki, Haibo Ding, Graham Neubig:
X-FACTR: Multilingual Factual Knowledge Retrieval from Pretrained Language Models. CoRR abs/2010.06189 (2020) - [i7]Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi, Zhengbao Jiang, Graham Neubig:
GSum: A General Framework for Guided Neural Abstractive Summarization. CoRR abs/2010.08014 (2020) - [i6]Zhengbao Jiang, Jun Araki, Haibo Ding, Graham Neubig:
How Can We Know When Language Models Know? CoRR abs/2012.00955 (2020)
2010 – 2019
- 2019
- [c3]Zhengbao Jiang, Pengcheng Yin, Graham Neubig:
Improving Open Information Extraction via Iterative Rank-Aware Learning. ACL (1) 2019: 5295-5300 - [i5]Zhengbao Jiang, Pengcheng Yin, Graham Neubig:
Improving Open Information Extraction via Iterative Rank-Aware Learning. CoRR abs/1905.13413 (2019) - [i4]Songwei Ge, Zhicheng Dou, Zhengbao Jiang, Jian-Yun Nie, Ji-Rong Wen:
Personalizing Search Results Using Hierarchical RNN with Query-aware Attention. CoRR abs/1908.07600 (2019) - [i3]Zhengbao Jiang, Wei Xu, Jun Araki, Graham Neubig:
Generalizing Natural Language Analysis through Span-relation Representations. CoRR abs/1911.03822 (2019) - [i2]Donghan Yu, Ruohong Zhang, Zhengbao Jiang, Yuexin Wu, Yiming Yang:
Graph-Revised Convolutional Network. CoRR abs/1911.07123 (2019) - [i1]Zhengbao Jiang, Frank F. Xu, Jun Araki, Graham Neubig:
How Can We Know What Language Models Know? CoRR abs/1911.12543 (2019) - 2018
- [j3]Zhengbao Jiang, Zhicheng Dou, Wayne Xin Zhao, Jian-Yun Nie, Ming Yue, Ji-Rong Wen:
Supervised Search Result Diversification via Subtopic Attention. IEEE Trans. Knowl. Data Eng. 30(10): 1971-1984 (2018) - [c2]Songwei Ge, Zhicheng Dou, Zhengbao Jiang, Jian-Yun Nie, Ji-Rong Wen:
Personalizing Search Results Using Hierarchical RNN with Query-aware Attention. CIKM 2018: 347-356 - 2017
- [j2]Zhengbao Jiang, Zhicheng Dou, Ji-Rong Wen:
Generating Query Facets Using Knowledge Bases. IEEE Trans. Knowl. Data Eng. 29(2): 315-329 (2017) - [c1]Zhengbao Jiang, Ji-Rong Wen, Zhicheng Dou, Wayne Xin Zhao, Jian-Yun Nie, Ming Yue:
Learning to Diversify Search Results via Subtopic Attention. SIGIR 2017: 545-554 - 2016
- [j1]Zhicheng Dou, Zhengbao Jiang, Sha Hu, Ji-Rong Wen, Ruihua Song:
Automatically Mining Facets for Queries from Their Search Results. IEEE Trans. Knowl. Data Eng. 28(2): 385-397 (2016)
Coauthor Index
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