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ORCIDPengfei Liu 0003
Person information
- affiliation: Shanghai Jiao Tong University, Generative AI Research Lab (GAIR), China
- affiliation (former): Carnegie Mellon University, PA, USA
- affiliation (former): Fudan University, Shanghai Key Laboratory of Intelligent Information Processing, China
Other persons with the same name
- Pengfei Liu (aka: PengFei Liu, Pengfeï Liu, Peng-Fei Liu) — disambiguation page
- Pengfei Liu 0001 — University of Bordeaux, France
- Pengfei Liu 0002
![[0000-0002-1603-3670]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-1603-3670")
— Nanjing University of Posts and Telecommunications, School of Computer Science, China
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Journal Articles
- 2023
[j2]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)- 2022
- [j1]Weizhe Yuan, Pengfei Liu, Graham Neubig:
Can We Automate Scientific Reviewing? J. Artif. Intell. Res. 75: 171-212 (2022)
Conference and Workshop Papers
- 2024
- [c76]Junlong Li, Fan Zhou, Shichao Sun, Yikai Zhang, Hai Zhao, Pengfei Liu:
Dissecting Human and LLM Preferences. ACL (1) 2024: 1790-1811 - [c75]Yan Ma, Yu Qiao, Pengfei Liu:
MoPS: Modular Story Premise Synthesis for Open-Ended Automatic Story Generation. ACL (1) 2024: 2135-2169 - [c74]Shichao Sun, Ruifeng Yuan, Ziqiang Cao, Wenjie Li, Pengfei Liu:
Prompt Chaining or Stepwise Prompt? Refinement in Text Summarization. ACL (Findings) 2024: 7551-7558 - [c73]Weizhe Yuan, Pengfei Liu, Matthias Gallé:
LLMCrit: Teaching Large Language Models to Use Criteria. ACL (Findings) 2024: 7929-7960 - [c72]Yiwei Qin, Kaiqiang Song, Yebowen Hu, Wenlin Yao, Sangwoo Cho, Xiaoyang Wang, Xuansheng Wu, Fei Liu, Pengfei Liu, Dong Yu:
InFoBench: Evaluating Instruction Following Ability in Large Language Models. ACL (Findings) 2024: 13025-13048 - [c71]Junlong Li, Shichao Sun, Weizhe Yuan, Run-Ze Fan, Hai Zhao, Pengfei Liu:
Generative Judge for Evaluating Alignment. ICLR 2024 - [c70]Jinlan Fu, See-Kiong Ng, Zhengbao Jiang, Pengfei Liu:
GPTScore: Evaluate as You Desire. NAACL-HLT 2024: 6556-6576 - [c69]Yixin Liu, Kejian Shi, Katherine He, Longtian Ye, Alexander R. Fabbri, Pengfei Liu, Dragomir Radev, Arman Cohan:
On Learning to Summarize with Large Language Models as References. NAACL-HLT 2024: 8647-8664 - 2023
- [c68]Yixin Liu, Alexander R. Fabbri, Pengfei Liu, Yilun Zhao, Linyong Nan, Ruilin Han, Simeng Han, Shafiq Joty, Chien-Sheng Wu, Caiming Xiong, Dragomir Radev:
Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation. ACL (1) 2023: 4140-4170 - [c67]Sameer Jain, Vaishakh Keshava, Swarnashree Mysore Sathyendra, Patrick Fernandes, Pengfei Liu, Graham Neubig, Chunting Zhou:
Multi-Dimensional Evaluation of Text Summarization with In-Context Learning. ACL (Findings) 2023: 8487-8495 - [c66]Vijay Viswanathan, Luyu Gao, Tongshuang Wu, Pengfei Liu, Graham Neubig:
DataFinder: Scientific Dataset Recommendation from Natural Language Descriptions. ACL (1) 2023: 10288-10303 - [c65]Yueqi Song, Simran Khanuja, Pengfei Liu, Fahim Faisal, Alissa Ostapenko, Genta Indra Winata, Alham Fikri Aji, Samuel Cahyawijaya, Yulia Tsvetkov, Antonios Anastasopoulos, Graham Neubig:
GlobalBench: A Benchmark for Global Progress in Natural Language Processing. EMNLP 2023: 14157-14171 - [c64]Yiwei Qin, Weizhe Yuan, Graham Neubig, Pengfei Liu:
T5Score: Discriminative Fine-tuning of Generative Evaluation Metrics. EMNLP (Findings) 2023: 15185-15202 - [c63]Yixin Liu, Alexander R. Fabbri, Yilun Zhao, Pengfei Liu, Shafiq Joty, Chien-Sheng Wu, Caiming Xiong, Dragomir Radev:
Towards Interpretable and Efficient Automatic Reference-Based Summarization Evaluation. EMNLP 2023: 16360-16368 - [c62]Luyu Gao, Aman Madaan, Shuyan Zhou, Uri Alon, Pengfei Liu, Yiming Yang, Jamie Callan, Graham Neubig:
PAL: Program-aided Language Models. ICML 2023: 10764-10799 - [c61]Yunxiang Li, Pengfei Liu, Xixin Wu, Helen Meng:
PunCantonese: A Benchmark Corpus for Low-Resource Cantonese Punctuation Restoration from Speech Transcripts. INTERSPEECH 2023: 2183-2187 - [c60]Shiqi Chen, Yiran Zhao, Jinghan Zhang, I-Chun Chern, Siyang Gao, Pengfei Liu, Junxian He:
FELM: Benchmarking Factuality Evaluation of Large Language Models. NeurIPS 2023 - 2022
- [c59]Weizhe Yuan, Pengfei Liu:
KID-Review: Knowledge-Guided Scientific Review Generation with Oracle Pre-training. AAAI 2022: 11639-11647 - [c58]Yang Xiao, Jinlan Fu, Weizhe Yuan, Vijay Viswanathan, Zhoumianze Liu, Yixin Liu, Graham Neubig, Pengfei Liu:
DataLab: A Platform for Data Analysis and Intervention. ACL (demo) 2022: 182-195 - [c57]Yixin Liu, Pengfei Liu, Dragomir R. Radev, Graham Neubig:
BRIO: Bringing Order to Abstractive Summarization. ACL (1) 2022: 2890-2903 - [c56]Haris Widjaja, Kiril Gashteovski, Wiem Ben Rim, Pengfei Liu, Christopher Malon, Daniel Ruffinelli, Carolin Lawrence, Graham Neubig:
KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Models. EMNLP (Demos) 2022: 338-350 - [c55]Ming Zhong, Yang Liu, Da Yin, Yuning Mao, Yizhu Jiao, Pengfei Liu, Chenguang Zhu, Heng Ji, Jiawei Han:
Towards a Unified Multi-Dimensional Evaluator for Text Generation. EMNLP 2022: 2023-2038 - [c54]Jinlan Fu, See-Kiong Ng, Pengfei Liu:
Polyglot Prompt: Multilingual Multitask Prompt Training. EMNLP 2022: 9919-9935 - [c53]HoLam Chung, Junan Li, Pengfei Liu, Wai-Kim Leung, Xixin Wu, Helen Meng:
Improving Rare Words Recognition through Homophone Extension and Unified Writing for Low-resource Cantonese Speech Recognition. ISCSLP 2022: 26-30 - [c52]Yang Xiao, Jinlan Fu, See-Kiong Ng, Pengfei Liu:
Are All the Datasets in Benchmark Necessary? A Pilot Study of Dataset Evaluation for Text Classification. NAACL-HLT 2022: 2930-2941 - 2021
- [c51]Pengfei Liu, Jinlan Fu, Yang Xiao, Weizhe Yuan, Shuaichen Chang, Junqi Dai, Yixin Liu, Zihuiwen Ye, Graham Neubig:
ExplainaBoard: An Explainable Leaderboard for NLP. ACL (demo) 2021: 280-289 - [c50]Vijay Viswanathan, Graham Neubig, Pengfei Liu:
CitationIE: Leveraging the Citation Graph for Scientific Information Extraction. ACL/IJCNLP (1) 2021: 719-731 - [c49]Yixin Liu, Pengfei Liu:
SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization. ACL/IJCNLP (2) 2021: 1065-1072 - [c48]Jinlan Fu, Xuanjing Huang, Pengfei Liu:
SpanNER: Named Entity Re-/Recognition as Span Prediction. ACL/IJCNLP (1) 2021: 7183-7195 - [c47]Zihuiwen Ye, Pengfei Liu, Jinlan Fu, Graham Neubig:
Towards More Fine-grained and Reliable NLP Performance Prediction. EACL 2021: 3703-3714 - [c46]Yiran Chen, Pengfei Liu, Xipeng Qiu:
Are Factuality Checkers Reliable? Adversarial Meta-evaluation of Factuality in Summarization. EMNLP (Findings) 2021: 2082-2095 - [c45]Sebastian Ruder, Noah Constant, Jan A. Botha, Aditya Siddhant, Orhan Firat, Jinlan Fu, Pengfei Liu, Junjie Hu, Dan Garrette, Graham Neubig, Melvin Johnson:
XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation. EMNLP (1) 2021: 10215-10245 - [c44]Guolei Jiang, Chunhong Liao, Kun Li, Pengfei Liu, Linying Jiang, Helen Meng:
Automatic Speaker-level Pronunciation Assessment of L2 Speech Using Posterior Probabilities from Multiple Utterances. ISCSLP 2021: 1-5 - [c43]Pengfei Liu, Kun Li, Helen Meng:
Out-of-Scope Domain and Intent Classification through Hierarchical Joint Modeling. IWSDS 2021: 3-16 - [c42]Yixin Liu, Zi-Yi Dou, Pengfei Liu:
RefSum: Refactoring Neural Summarization. NAACL-HLT 2021: 1437-1448 - [c41]Jinlan Fu, Liangjing Feng, Qi Zhang, Xuanjing Huang, Pengfei Liu:
Larger-Context Tagging: When and Why Does It Work? NAACL-HLT 2021: 1463-1475 - [c40]Junqi Dai, Hang Yan, Tianxiang Sun, Pengfei Liu, Xipeng Qiu:
Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTa. NAACL-HLT 2021: 1816-1829 - [c39]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 - [c38]Weizhe Yuan, Graham Neubig, Pengfei Liu:
BARTScore: Evaluating Generated Text as Text Generation. NeurIPS 2021: 27263-27277 - 2020
- [c37]Jinlan Fu, Pengfei Liu, Qi Zhang:
Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study. AAAI 2020: 7732-7739 - [c36]Qipeng Guo, Xipeng Qiu, Pengfei Liu, Xiangyang Xue, Zheng Zhang:
Multi-Scale Self-Attention for Text Classification. AAAI 2020: 7847-7854 - [c35]Tianxiang Sun, Yunfan Shao, Xiaonan Li, Pengfei Liu, Hang Yan, Xipeng Qiu, Xuanjing Huang:
Learning Sparse Sharing Architectures for Multiple Tasks. AAAI 2020: 8936-8943 - [c34]Ming Zhong, Pengfei Liu, Yiran Chen, Danqing Wang, Xipeng Qiu, Xuanjing Huang:
Extractive Summarization as Text Matching. ACL 2020: 6197-6208 - [c33]Danqing Wang, Pengfei Liu, Yining Zheng, Xipeng Qiu, Xuanjing Huang:
Heterogeneous Graph Neural Networks for Extractive Document Summarization. ACL 2020: 6209-6219 - [c32]Yiran Chen, Pengfei Liu, Ming Zhong, Zi-Yi Dou, Danqing Wang, Xipeng Qiu, Xuanjing Huang:
An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems. EMNLP (Findings) 2020: 3679-3691 - [c31]Jinlan Fu, Pengfei Liu, Qi Zhang, Xuanjing Huang:
RethinkCWS: Is Chinese Word Segmentation a Solved Task? EMNLP (1) 2020: 5676-5686 - [c30]Jinlan Fu, Pengfei Liu, Graham Neubig:
Interpretable Multi-dataset Evaluation for Named Entity Recognition. EMNLP (1) 2020: 6058-6069 - [c29]Manik Bhandari, Pranav Narayan Gour, Atabak Ashfaq, Pengfei Liu, Graham Neubig:
Re-evaluating Evaluation in Text Summarization. EMNLP (1) 2020: 9347-9359 - [c28]Pengfei Liu, Kun Li, Helen Meng:
Group Gated Fusion on Attention-Based Bidirectional Alignment for Multimodal Emotion Recognition. INTERSPEECH 2020: 379-383 - 2019
- [c27]Pengfei Liu, Jie Fu, Yue Dong, Xipeng Qiu, Jackie Chi Kit Cheung:
Learning Multi-Task Communication with Message Passing for Sequence Learning. AAAI 2019: 4360-4367 - [c26]Pengfei Liu, Shuaichen Chang, Xuanjing Huang, Jian Tang, Jackie Chi Kit Cheung:
Contextualized Non-Local Neural Networks for Sequence Learning. AAAI 2019: 6762-6769 - [c25]Ming Zhong, Pengfei Liu, Danqing Wang, Xipeng Qiu, Xuanjing Huang:
Searching for Effective Neural Extractive Summarization: What Works and What's Next. ACL (1) 2019: 1049-1058 - [c24]Dayiheng Liu, Jie Fu, Pengfei Liu, Jiancheng Lv:
TIGS: An Inference Algorithm for Text Infilling with Gradient Search. ACL (1) 2019: 4146-4156 - [c23]Qipeng Guo, Xipeng Qiu, Pengfei Liu, Yunfan Shao, Xiangyang Xue, Zheng Zhang:
Star-Transformer. NAACL-HLT (1) 2019: 1315-1325 - 2018
- [c22]Junkun Chen, Xipeng Qiu, Pengfei Liu, Xuanjing Huang:
Meta Multi-Task Learning for Sequence Modeling. AAAI 2018: 5070-5077 - 2017
- [c21]Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Adversarial Multi-task Learning for Text Classification. ACL (1) 2017: 1-10 - [c20]Pengfei Liu, Kaiyu Qian, Xipeng Qiu, Xuanjing Huang:
Idiom-Aware Compositional Distributed Semantics. EMNLP 2017: 1204-1213 - [c19]Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Dynamic Compositional Neural Networks over Tree Structure. IJCAI 2017: 4054-4060 - [c18]Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Adaptive Semantic Compositionality for Sentence Modelling. IJCAI 2017: 4061-4067 - [c17]Pengfei Liu, King Keung Wu, Helen M. Meng:
A model of extended paragraph vector for document categorization and trend analysis. IJCNN 2017: 2400-2406 - 2016
- [c16]Jifan Chen, Qi Zhang, Pengfei Liu, Xuanjing Huang:
Discourse Relations Detection via a Mixed Generative-Discriminative Framework. AAAI 2016: 2921-2927 - [c15]Jifan Chen, Qi Zhang, Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Implicit Discourse Relation Detection via a Deep Architecture with Gated Relevance Network. ACL (1) 2016 - [c14]Pengfei Liu, Xipeng Qiu, Jifan Chen, Xuanjing Huang:
Deep Fusion LSTMs for Text Semantic Matching. ACL (1) 2016 - [c13]Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Deep Multi-Task Learning with Shared Memory for Text Classification. EMNLP 2016: 118-127 - [c12]Pengfei Liu, Xipeng Qiu, Yaqian Zhou, Jifan Chen, Xuanjing Huang:
Modelling Interaction of Sentence Pair with Coupled-LSTMs. EMNLP 2016: 1703-1712 - [c11]Pengfei Liu, Shoaib Jameel, King Keung Wu, Helen M. Meng:
Learning Track Representation and Trends for Conference Analytics. HICSS 2016: 1671-1680 - [c10]Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Recurrent Neural Network for Text Classification with Multi-Task Learning. IJCAI 2016: 2873-2879 - [c9]King Keung Wu, Pengfei Liu, Helen M. Meng, Yeung Yam:
An embedding approach for context-aware collaborative recommendation and visualization. SMC 2016: 3457-3462 - 2015
- [c8]Xinchi Chen, Xipeng Qiu, Chenxi Zhu, Pengfei Liu, Xuanjing Huang:
Long Short-Term Memory Neural Networks for Chinese Word Segmentation. EMNLP 2015: 1197-1206 - [c7]Pengfei Liu, Shafiq R. Joty, Helen M. Meng:
Fine-grained Opinion Mining with Recurrent Neural Networks and Word Embeddings. EMNLP 2015: 1433-1443 - [c6]Pengfei Liu, Xipeng Qiu, Xinchi Chen, Shiyu Wu, Xuanjing Huang:
Multi-Timescale Long Short-Term Memory Neural Network for Modelling Sentences and Documents. EMNLP 2015: 2326-2335 - [c5]Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Learning Context-Sensitive Word Embeddings with Neural Tensor Skip-Gram Model. IJCAI 2015: 1284-1290 - [c4]Pengfei Liu, Shoaib Jameel, Wai Lam, Bin Ma, Helen M. Meng:
Topic modeling for conference analytics. INTERSPEECH 2015: 707-711 - [c3]Kun Li, Xiaojun Qian, Shiyin Kang, Pengfei Liu, Helen Meng:
Integrating acoustic and state-transition models for free phone recognition in L2 English speech using multi-distribution deep neural networks. SLaTE 2015: 119-124 - 2014
- [c2]Pengfei Liu, Helen M. Meng:
SeemGo: Conditional Random Fields Labeling and Maximum Entropy Classification for Aspect Based Sentiment Analysis. SemEval@COLING 2014: 527-531 - 2012
- [c1]Pengfei Liu, Ka-Wa Yuen, Wai-Kim Leung, Helen M. Meng:
mENUNCIATE: Development of a computer-aided pronunciation training system on a cross-platform framework for mobile, speech-enabled application development. ISCSLP 2012: 170-173
Editorship
- 2022
- [e3]Yulan He, Heng Ji, Yang Liu, Sujian Li, Chia-Hui Chang, Soujanya Poria, Chenghua Lin, Wray L. Buntine, Maria Liakata, Hanqi Yan, Zonghan Yan, Sebastian Ruder, Xiaojun Wan, Miguel Arana-Catania, Zhongyu Wei, Hen-Hsen Huang, Jheng-Long Wu, Min-Yuh Day, Pengfei Liu, Ruifeng Xu:
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, AACL/IJCNLP 2022 - Volume 1: Long Papers, Online Only, November 20-23, 2022. Association for Computational Linguistics 2022, ISBN 978-1-955917-65-0 [contents] - [e2]Yulan He, Heng Ji, Yang Liu, Sujian Li, Chia-Hui Chang, Soujanya Poria, Chenghua Lin, Wray L. Buntine, Maria Liakata, Hanqi Yan, Zonghan Yan, Sebastian Ruder, Xiaojun Wan, Miguel Arana-Catania, Zhongyu Wei, Hen-Hsen Huang, Jheng-Long Wu, Min-Yuh Day, Pengfei Liu, Ruifeng Xu:
Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, AACL/IJCNLP 2022 - Volume 2: Short Papers, Online only, November 20-23, 2022. Association for Computational Linguistics 2022, ISBN 978-1-955917-64-3 [contents] - [e1]Yulan He, Heng Ji, Yang Liu, Sujian Li, Chia-Hui Chang, Soujanya Poria, Chenghua Lin, Wray L. Buntine, Maria Liakata, Hanqi Yan, Zonghan Yan, Sebastian Ruder, Xiaojun Wan, Miguel Arana-Catania, Zhongyu Wei, Hen-Hsen Huang, Jheng-Long Wu, Min-Yuh Day, Pengfei Liu, Ruifeng Xu:
Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022, Online only, November 20-23, 2022. Association for Computational Linguistics 2022, ISBN 978-1-959429-04-3 [contents]
Informal and Other Publications
- 2024
- [i87]Yiwei Qin, Kaiqiang Song, Yebowen Hu, Wenlin Yao, Sangwoo Cho, Xiaoyang Wang, Xuansheng Wu, Fei Liu, Pengfei Liu, Dong Yu:
InFoBench: Evaluating Instruction Following Ability in Large Language Models. CoRR abs/2401.03601 (2024) - [i86]Shichao Sun, Junlong Li, Weizhe Yuan, Ruifeng Yuan, Wenjie Li, Pengfei Liu:
The Critique of Critique. CoRR abs/2401.04518 (2024) - [i85]Yikai Zhang, Junlong Li, Pengfei Liu:
Extending LLMs' Context Window with 100 Samples. CoRR abs/2401.07004 (2024) - [i84]Steffi Chern, Ethan Chern, Graham Neubig, Pengfei Liu:
Can Large Language Models be Trusted for Evaluation? Scalable Meta-Evaluation of LLMs as Evaluators via Agent Debate. CoRR abs/2401.16788 (2024) - [i83]Junlong Li, Fan Zhou, Shichao Sun, Yikai Zhang, Hai Zhao, Pengfei Liu:
Dissecting Human and LLM Preferences. CoRR abs/2402.11296 (2024) - [i82]Run-Ze Fan, Xuefeng Li, Haoyang Zou, Junlong Li, Shwai He, Ethan Chern, Jiewen Hu, Pengfei Liu:
Reformatted Alignment. CoRR abs/2402.12219 (2024) - [i81]Weizhe Yuan, Pengfei Liu, Matthias Gallé:
LLMCRIT: Teaching Large Language Models to Use Criteria. CoRR abs/2403.01069 (2024) - [i80]Shijie Xia, Xuefeng Li, Yixin Liu, Tongshuang Wu, Pengfei Liu:
Evaluating Mathematical Reasoning Beyond Accuracy. CoRR abs/2404.05692 (2024) - [i79]Ruijie Xu, Zengzhi Wang, Run-Ze Fan, Pengfei Liu:
Benchmarking Benchmark Leakage in Large Language Models. CoRR abs/2404.18824 (2024) - [i78]Shichao Sun, Ruifeng Yuan, Ziqiang Cao, Wenjie Li, Pengfei Liu:
Prompt Chaining or Stepwise Prompt? Refinement in Text Summarization. CoRR abs/2406.00507 (2024) - [i77]Zhen Huang, Zengzhi Wang, Shijie Xia, Xuefeng Li, Haoyang Zou, Ruijie Xu, Run-Ze Fan, Lyumanshan Ye, Ethan Chern, Yixin Ye, Yikai Zhang, Yuqing Yang, Ting Wu, Binjie Wang, Shichao Sun, Yang Xiao, Yiyuan Li, Fan Zhou, Steffi Chern, Yiwei Qin, Yan Ma, Jiadi Su, Yixiu Liu, Yuxiang Zheng, Shaoting Zhang, Dahua Lin, Yu Qiao, Pengfei Liu:
OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI. CoRR abs/2406.12753 (2024) - [i76]Steffi Chern, Zhulin Hu, Yuqing Yang, Ethan Chern, Yuan Guo, Jiahe Jin, Binjie Wang, Pengfei Liu:
BeHonest: Benchmarking Honesty of Large Language Models. CoRR abs/2406.13261 (2024) - [i75]Zhen Huang, Zengzhi Wang, Shijie Xia, Pengfei Liu:
OlympicArena Medal Ranks: Who Is the Most Intelligent AI So Far? CoRR abs/2406.16772 (2024) - [i74]Yiyuan Li, Shichao Sun, Pengfei Liu:
FRoG: Evaluating Fuzzy Reasoning of Generalized Quantifiers in Large Language Models. CoRR abs/2407.01046 (2024) - [i73]Ting Wu, Xuefeng Li, Pengfei Liu:
Progress or Regress? Self-Improvement Reversal in Post-training. CoRR abs/2407.05013 (2024) - [i72]Ethan Chern, Jiadi Su, Yan Ma, Pengfei Liu:
ANOLE: An Open, Autoregressive, Native Large Multimodal Models for Interleaved Image-Text Generation. CoRR abs/2407.06135 (2024) - [i71]Mianxin Liu, Jinru Ding, Jie Xu, Weiguo Hu, Xiaoyang Li, Lifeng Zhu, Zhian Bai, Xiaoming Shi, Benyou Wang, Haitao Song, Pengfei Liu, Xiaofan Zhang, Shanshan Wang, Kang Li, Haofen Wang, Tong Ruan, Xuanjing Huang, Xin Sun, Shaoting Zhang:
MedBench: A Comprehensive, Standardized, and Reliable Benchmarking System for Evaluating Chinese Medical Large Language Models. CoRR abs/2407.10990 (2024) - [i70]Binjie Wang, Steffi Chern, Ethan Chern, Pengfei Liu:
Halu-J: Critique-Based Hallucination Judge. CoRR abs/2407.12943 (2024) - [i69]Yuqing Yang, Yan Ma, Pengfei Liu:
Weak-to-Strong Reasoning. CoRR abs/2407.13647 (2024) - [i68]Yixin Liu, Pengfei Liu, Arman Cohan:
Understanding Reference Policies in Direct Preference Optimization. CoRR abs/2407.13709 (2024) - 2023
- [i67]HoLam Chung, Junan Li, Pengfei Liu, Wai-Kim Leung, Xixin Wu, Helen Meng:
Improving Rare Words Recognition through Homophone Extension and Unified Writing for Low-resource Cantonese Speech Recognition. CoRR abs/2302.00836 (2023) - [i66]Jinlan Fu, See-Kiong Ng, Zhengbao Jiang, Pengfei Liu:
GPTScore: Evaluate as You Desire. CoRR abs/2302.04166 (2023) - [i65]Yixin Liu, Alexander R. Fabbri, Yilun Zhao, Pengfei Liu, Shafiq R. Joty, Chien-Sheng Wu, Caiming Xiong, Dragomir Radev:
Towards Interpretable and Efficient Automatic Reference-Based Summarization Evaluation. CoRR abs/2303.03608 (2023) - [i64]Yixin Liu, Alexander R. Fabbri, Pengfei Liu, Dragomir Radev, Arman Cohan:
On Learning to Summarize with Large Language Models as References. CoRR abs/2305.14239 (2023) - [i63]Yueqi Song, Catherine Cui, Simran Khanuja, Pengfei Liu, Fahim Faisal, Alissa Ostapenko, Genta Indra Winata, Alham Fikri Aji, Samuel Cahyawijaya, Yulia Tsvetkov, Antonios Anastasopoulos, Graham Neubig:
GlobalBench: A Benchmark for Global Progress in Natural Language Processing. CoRR abs/2305.14716 (2023) - [i62]Vijay Viswanathan, Luyu Gao, Tongshuang Wu, Pengfei Liu, Graham Neubig:
DataFinder: Scientific Dataset Recommendation from Natural Language Descriptions. CoRR abs/2305.16636 (2023) - [i61]Sameer Jain, Vaishakh Keshava, Swarnashree Mysore Sathyendra, Patrick Fernandes, Pengfei Liu, Graham Neubig, Chunting Zhou:
Multi-Dimensional Evaluation of Text Summarization with In-Context Learning. CoRR abs/2306.01200 (2023) - [i60]I-Chun Chern, Zhiruo Wang, Sanjan Das, Bhavuk Sharma, Pengfei Liu, Graham Neubig:
Improving Factuality of Abstractive Summarization via Contrastive Reward Learning. CoRR abs/2307.04507 (2023) - [i59]I-Chun Chern, Steffi Chern, Shiqi Chen, Weizhe Yuan, Kehua Feng, Chunting Zhou, Junxian He, Graham Neubig, Pengfei Liu:
FacTool: Factuality Detection in Generative AI - A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios. CoRR abs/2307.13528 (2023) - [i58]Shiqi Chen, Yiran Zhao, Jinghan Zhang, I-Chun Chern, Siyang Gao, Pengfei Liu, Junxian He:
FELM: Benchmarking Factuality Evaluation of Large Language Models. CoRR abs/2310.00741 (2023) - [i57]Junlong Li, Shichao Sun, Weizhe Yuan, Run-Ze Fan, Hai Zhao, Pengfei Liu:
Generative Judge for Evaluating Alignment. CoRR abs/2310.05470 (2023) - [i56]Yixin Liu, Alexander R. Fabbri, Jiawen Chen, Yilun Zhao, Simeng Han, Shafiq Joty, Pengfei Liu, Dragomir Radev, Chien-Sheng Wu, Arman Cohan:
Benchmarking Generation and Evaluation Capabilities of Large Language Models for Instruction Controllable Summarization. CoRR abs/2311.09184 (2023) - [i55]Yuqing Yang, Ethan Chern, Xipeng Qiu, Graham Neubig, Pengfei Liu:
Alignment for Honesty. CoRR abs/2312.07000 (2023) - [i54]Chunpu Xu, Steffi Chern, Ethan Chern, Ge Zhang, Zekun Wang, Ruibo Liu, Jing Li, Jie Fu, Pengfei Liu:
Align on the Fly: Adapting Chatbot Behavior to Established Norms. CoRR abs/2312.15907 (2023) - [i53]Zengzhi Wang, Rui Xia, Pengfei Liu:
Generative AI for Math: Part I - MathPile: A Billion-Token-Scale Pretraining Corpus for Math. CoRR abs/2312.17120 (2023) - 2022
- [i52]Pengfei Liu, Kun Li, Helen Meng:
Group Gated Fusion on Attention-based Bidirectional Alignment for Multimodal Emotion Recognition. CoRR abs/2201.06309 (2022) - [i51]Yang Xiao, Jinlan Fu, Weizhe Yuan, Vijay Viswanathan, Zhoumianze Liu, Yixin Liu, Graham Neubig, Pengfei Liu:
DataLab: A Platform for Data Analysis and Intervention. CoRR abs/2202.12875 (2022) - [i50]Yixin Liu, Pengfei Liu, Dragomir R. Radev, Graham Neubig:
BRIO: Bringing Order to Abstractive Summarization. CoRR abs/2203.16804 (2022) - [i49]Jinlan Fu, See-Kiong Ng, Pengfei Liu:
Polyglot Prompt: Multilingual Multitask PrompTraining. CoRR abs/2204.14264 (2022) - [i48]Yang Xiao, Jinlan Fu, See-Kiong Ng, Pengfei Liu:
Are All the Datasets in Benchmark Necessary? A Pilot Study of Dataset Evaluation for Text Classification. CoRR abs/2205.02129 (2022) - [i47]Weizhe Yuan, Pengfei Liu:
reStructured Pre-training. CoRR abs/2206.11147 (2022) - [i46]Haris Widjaja, Kiril Gashteovski, Wiem Ben Rim, Pengfei Liu, Christopher Malon, Daniel Ruffinelli, Carolin Lawrence, Graham Neubig:
KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Models. CoRR abs/2208.11024 (2022) - [i45]Ming Zhong, Yang Liu, Da Yin, Yuning Mao, Yizhu Jiao, Pengfei Liu, Chenguang Zhu, Heng Ji, Jiawei Han:
Towards a Unified Multi-Dimensional Evaluator for Text Generation. CoRR abs/2210.07197 (2022) - [i44]Luyu Gao, Aman Madaan, Shuyan Zhou, Uri Alon, Pengfei Liu, Yiming Yang, Jamie Callan, Graham Neubig:
PAL: Program-aided Language Models. CoRR abs/2211.10435 (2022) - [i43]Yiwei Qin, Weizhe Yuan, Graham Neubig, Pengfei Liu:
T5Score: Discriminative Fine-tuning of Generative Evaluation Metrics. CoRR abs/2212.05726 (2022) - [i42]Yiwei Qin, Graham Neubig, Pengfei Liu:
Searching for Effective Multilingual Fine-Tuning Methods: A Case Study in Summarization. CoRR abs/2212.05740 (2022) - [i41]Yixin Liu, Alexander R. Fabbri, Pengfei Liu, Yilun Zhao, Linyong Nan, Ruilin Han, Simeng Han, Shafiq R. Joty, Chien-Sheng Wu, Caiming Xiong, Dragomir Radev:
Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation. CoRR abs/2212.07981 (2022) - 2021
- [i40]Weizhe Yuan, Pengfei Liu, Graham Neubig:
Can We Automate Scientific Reviewing? CoRR abs/2102.00176 (2021) - [i39]Zihuiwen Ye, Pengfei Liu, Jinlan Fu, Graham Neubig:
Towards More Fine-grained and Reliable NLP Performance Prediction. CoRR abs/2102.05486 (2021) - [i38]Jinlan Fu, Liangjing Feng, Qi Zhang, Xuanjing Huang, Pengfei Liu:
Larger-Context Tagging: When and Why Does It Work? CoRR abs/2104.04434 (2021) - [i37]Junqi Dai, Hang Yan, Tianxiang Sun, Pengfei Liu, Xipeng Qiu:
Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTa. CoRR abs/2104.04986 (2021) - [i36]Pengfei Liu, Jinlan Fu, Yang Xiao, Weizhe Yuan, Shuaichen Chang, Junqi Dai, Yixin Liu, Zihuiwen Ye, Graham Neubig:
EXPLAINABOARD: An Explainable Leaderboard for NLP. CoRR abs/2104.06387 (2021) - [i35]Yixin Liu, Zi-Yi Dou, Pengfei Liu:
RefSum: Refactoring Neural Summarization. CoRR abs/2104.07210 (2021) - [i34]Sebastian Ruder, Noah Constant, Jan A. Botha, Aditya Siddhant, Orhan Firat, Jinlan Fu, Pengfei Liu, Junjie Hu, Graham Neubig, Melvin Johnson:
XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation. CoRR abs/2104.07412 (2021) - [i33]Pengfei Liu, Youzhang Ning, King Keung Wu, Kun Li, Helen Meng:
Open Intent Discovery through Unsupervised Semantic Clustering and Dependency Parsing. CoRR abs/2104.12114 (2021) - [i32]Pengfei Liu, Kun Li, Helen Meng:
Hierarchical Modeling for Out-of-Scope Domain and Intent Classification. CoRR abs/2104.14781 (2021) - [i31]Jinlan Fu, Xuanjing Huang, Pengfei Liu:
SpanNER: Named Entity Re-/Recognition as Span Prediction. CoRR abs/2106.00641 (2021) - [i30]Vijay Viswanathan, Graham Neubig, Pengfei Liu:
CitationIE: Leveraging the Citation Graph for Scientific Information Extraction. CoRR abs/2106.01560 (2021) - [i29]Yixin Liu, Pengfei Liu:
SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization. CoRR abs/2106.01890 (2021) - [i28]Weizhe Yuan, Graham Neubig, Pengfei Liu:
BARTScore: Evaluating Generated Text as Text Generation. CoRR abs/2106.11520 (2021) - [i27]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
- [i26]Jinlan Fu, Pengfei Liu, Qi Zhang, Xuanjing Huang:
Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study. CoRR abs/2001.03844 (2020) - [i25]Ming Zhong, Pengfei Liu, Yiran Chen, Danqing Wang, Xipeng Qiu, Xuanjing Huang:
Extractive Summarization as Text Matching. CoRR abs/2004.08795 (2020) - [i24]Danqing Wang, Pengfei Liu, Yining Zheng, Xipeng Qiu, Xuanjing Huang:
Heterogeneous Graph Neural Networks for Extractive Document Summarization. CoRR abs/2004.12393 (2020) - [i23]Yiran Chen, Pengfei Liu, Ming Zhong, Zi-Yi Dou, Danqing Wang, Xipeng Qiu, Xuanjing Huang:
CDEvalSumm: An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems. CoRR abs/2010.05139 (2020) - [i22]Manik Bhandari, Pranav Narayan Gour, Atabak Ashfaq, Pengfei Liu, Graham Neubig:
Re-evaluating Evaluation in Text Summarization. CoRR abs/2010.07100 (2020) - [i21]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) - [i20]Jinlan Fu, Pengfei Liu, Graham Neubig:
Interpretable Multi-dataset Evaluation for Named Entity Recognition. CoRR abs/2011.06854 (2020) - [i19]Jinlan Fu, Pengfei Liu, Qi Zhang, Xuanjing Huang:
RethinkCWS: Is Chinese Word Segmentation a Solved Task? CoRR abs/2011.06858 (2020) - 2019
- [i18]Qipeng Guo, Xipeng Qiu, Pengfei Liu, Yunfan Shao, Xiangyang Xue, Zheng Zhang:
Star-Transformer. CoRR abs/1902.09113 (2019) - [i17]Dayiheng Liu, Jie Fu, Pengfei Liu, Jiancheng Lv:
TIGS: An Inference Algorithm for Text Infilling with Gradient Search. CoRR abs/1905.10752 (2019) - [i16]Ming Zhong, Pengfei Liu, Danqing Wang, Xipeng Qiu, Xuanjing Huang:
Searching for Effective Neural Extractive Summarization: What Works and What's Next. CoRR abs/1907.03491 (2019) - [i15]Zehui Lin, Pengfei Liu, Luyao Huang, Junkun Chen, Xipeng Qiu, Xuanjing Huang:
DropAttention: A Regularization Method for Fully-Connected Self-Attention Networks. CoRR abs/1907.11065 (2019) - [i14]Danqing Wang, Pengfei Liu, Ming Zhong, Jie Fu, Xipeng Qiu, Xuanjing Huang:
Exploring Domain Shift in Extractive Text Summarization. CoRR abs/1908.11664 (2019) - [i13]Ming Zhong, Danqing Wang, Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
A Closer Look at Data Bias in Neural Extractive Summarization Models. CoRR abs/1909.13705 (2019) - [i12]Tianxiang Sun, Yunfan Shao, Xiaonan Li, Pengfei Liu, Hang Yan, Xipeng Qiu, Xuanjing Huang:
Learning Sparse Sharing Architectures for Multiple Tasks. CoRR abs/1911.05034 (2019) - [i11]Qipeng Guo, Xipeng Qiu, Pengfei Liu, Xiangyang Xue, Zheng Zhang:
Multi-Scale Self-Attention for Text Classification. CoRR abs/1912.00544 (2019) - 2018
- [i10]Junkun Chen, Xipeng Qiu, Pengfei Liu, Xuanjing Huang:
Meta Multi-Task Learning for Sequence Modeling. CoRR abs/1802.08969 (2018) - [i9]Pengfei Liu, Xuanjing Huang:
Meta-Learning Multi-task Communication. CoRR abs/1810.09988 (2018) - [i8]Pengfei Liu, Shuaichen Chang, Xuanjing Huang, Jian Tang, Jackie Chi Kit Cheung:
Contextualized Non-local Neural Networks for Sequence Learning. CoRR abs/1811.08600 (2018) - [i7]Pengfei Liu, Jie Fu, Yue Dong, Xipeng Qiu, Jackie Chi Kit Cheung:
Multi-task Learning over Graph Structures. CoRR abs/1811.10211 (2018) - 2017
- [i6]Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Adversarial Multi-task Learning for Text Classification. CoRR abs/1704.05742 (2017) - [i5]Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Dynamic Compositional Neural Networks over Tree Structure. CoRR abs/1705.04153 (2017) - 2016
- [i4]Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Recurrent Neural Network for Text Classification with Multi-Task Learning. CoRR abs/1605.05101 (2016) - [i3]Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Modelling Interaction of Sentence Pair with coupled-LSTMs. CoRR abs/1605.05573 (2016) - [i2]Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Syntax-based Attention Model for Natural Language Inference. CoRR abs/1607.06556 (2016) - [i1]Pengfei Liu, Xipeng Qiu, Xuanjing Huang:
Deep Multi-Task Learning with Shared Memory. CoRR abs/1609.07222 (2016)
Coauthor Index
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