The design and implementation of the 1911 revolution ontology search engine. - Junmin Ye; Pengcheng He; Shizi Li; Jingru Chen; Tong Tian (FSKD, 2012)

Low illumination image Retinex enhancement algorithm based on guided filtering. - Jingcao Yin; Hongbo Li 001; Junping Du 001; Pengcheng He (CCIS, 2014)

Scalable Deep Document / Sequence Reasoning with Cognitive Toolkit. - Sayan Pathak; Pengcheng He; William Darling (WWW (Companion Volume), 2017)

3D Spatial Pyramid Dilated Network for Pulmonary Nodule Classification. - Guokai Zhang; Xiao Liu 030; Dandan Zhu; Pengcheng He; Lipeng Liang; Ye Luo; Jianwei Lu (Symmetry, 2018)

Multi-Task Deep Neural Networks for Natural Language Understanding. - Xiaodong Liu 003; Pengcheng He; Weizhu Chen; Jianfeng Gao 001 (ACL (1), 2019)

A Bi-Attention Adversarial Network for Prostate Cancer Segmentation. - Guokai Zhang; Weigang Wang; Dinghao Yang; Jihao Luo; Pengcheng He; Yongtong Wang; Ye Luo; Binghui Zhao; Jianwei Lu (IEEE Access, 2019)

Improving Multi-Task Deep Neural Networks via Knowledge Distillation for Natural Language Understanding. - Xiaodong Liu 003; Pengcheng He; Weizhu Chen; Jianfeng Gao 001 (CoRR, 2019)

A Hybrid Neural Network Model for Commonsense Reasoning. - Pengcheng He; Xiaodong Liu 003; Weizhu Chen; Jianfeng Gao 001 (CoRR, 2019)

X-SQL: reinforce schema representation with context. - Pengcheng He; Yi Mao; Kaushik Chakrabarti; Weizhu Chen (CoRR, 2019)

SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization. - Haoming Jiang; Pengcheng He; Weizhu Chen; Xiaodong Liu 003; Jianfeng Gao 001; Tuo Zhao (ACL, 2020)

The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding. - Xiaodong Liu 003; Yu Wang 009; Jianshu Ji; Hao Cheng 002; Xueyun Zhu; Emmanuel Awa; Pengcheng He; Weizhu Chen; Hoifung Poon; Guihong Cao; Jianfeng Gao 001 (ACL (demo), 2020)

Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning. - Tao Shen 001; Yi Mao; Pengcheng He; Guodong Long; Adam Trischler; Weizhu Chen (EMNLP (1), 2020)

On the Variance of the Adaptive Learning Rate and Beyond. - Liyuan Liu; Haoming Jiang; Pengcheng He; Weizhu Chen; Xiaodong Liu 003; Jianfeng Gao 001; Jiawei Han 001 (ICLR, 2020)

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. - Sewon Min; Jordan L. Boyd-Graber; Chris Alberti; Danqi Chen 001; Eunsol Choi; Michael Collins 001; Kelvin Guu; Hannaneh Hajishirzi; Kenton Lee; Jennimaria Palomaki; Colin Raffel; Adam Roberts; et al. (NeurIPS (Competition and Demos), 2020)

Robust TOA-Based Source Self-Positioning With Clock Imperfection. - Pengcheng He; Xiaohu Jiang; Qingjiang Shi (WCNC, 2020)

Adversarial Training for Large Neural Language Models. - Xiaodong Liu 003; Hao Cheng 002; Pengcheng He; Weizhu Chen; Yu Wang 009; Hoifung Poon; Jianfeng Gao 001 (CoRR, 2020)

UnitedQA: A Hybrid Approach for Open Domain Question Answering. - Hao Cheng 002; Yelong Shen; Xiaodong Liu 003; Pengcheng He; Weizhu Chen; Jianfeng Gao 001 (ACL/IJCNLP (1), 2021)

Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. - Chen Liang 006; Simiao Zuo; Minshuo Chen; Haoming Jiang; Xiaodong Liu 003; Pengcheng He; Tuo Zhao; Weizhu Chen (ACL/IJCNLP (1), 2021)

Generation-Augmented Retrieval for Open-Domain Question Answering. - Yuning Mao; Pengcheng He; Xiaodong Liu 003; Yelong Shen; Jianfeng Gao 001; Jiawei Han 001; Weizhu Chen (ACL/IJCNLP (1), 2021)

Reader-Guided Passage Reranking for Open-Domain Question Answering. - Yuning Mao; Pengcheng He; Xiaodong Liu 003; Yelong Shen; Jianfeng Gao 001; Jiawei Han 001; Weizhu Chen (ACL/IJCNLP (Findings), 2021)

Research on Distributed Amplifier Circuit Based on CMOS Process. - Pengcheng He (CONF-SPML, 2021)

Irregular Flight Timetable Recovery Under COVID-19: An Approach Based on Genetic Algorithm. - Tianwei Zhou; Junrui Lu; Wenwen Zhang; Pengcheng He; Ben Niu 002 (DMBD (1), 2021)

Token-wise Curriculum Learning for Neural Machine Translation. - Chen Liang 006; Haoming Jiang; Xiaodong Liu 003; Pengcheng He; Weizhu Chen; Jianfeng Gao 001; Tuo Zhao (EMNLP (Findings), 2021)

ARCH: Efficient Adversarial Regularized Training with Caching. - Simiao Zuo; Chen Liang 006; Haoming Jiang; Pengcheng He; Xiaodong Liu 003; Jianfeng Gao 001; Weizhu Chen; Tuo Zhao (EMNLP (Findings), 2021)

Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach. - Simiao Zuo; Chen Liang 006; Haoming Jiang; Xiaodong Liu 003; Pengcheng He; Jianfeng Gao 001; Weizhu Chen; Tuo Zhao (EMNLP (1), 2021)

Deberta: decoding-Enhanced Bert with Disentangled Attention. - Pengcheng He; Xiaodong Liu 003; Jianfeng Gao 001; Weizhu Chen (ICLR, 2021)

Greedy Multi-step Off-Policy Reinforcement Learning. - Yuhui Wang 004; Pengcheng He; Xiaoyang Tan (CoRR, 2021)

Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach. - Simiao Zuo; Chen Liang 006; Haoming Jiang; Xiaodong Liu 003; Pengcheng He; Jianfeng Gao 001; Weizhu Chen; Tuo Zhao (CoRR, 2021)

A Novel Image Encryption Algorithm Based on the Delayed Maps and Permutation-Confusion-Diffusion Architecture. - Pengcheng He; Kehui Sun; Congxu Zhu (Secur. Commun. Networks, 2021)

CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing. - Chen Liang 006; Pengcheng He; Yelong Shen; Weizhu Chen; Tuo Zhao (ACL (1), 2022)

No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. - Chen Liang 006; Haoming Jiang; Simiao Zuo; Pengcheng He; Xiaodong Liu 003; Jianfeng Gao 001; Weizhu Chen; Tuo Zhao (ICLR, 2022)

PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. - Qingru Zhang; Simiao Zuo; Chen Liang 006; Alexander Bukharin; Pengcheng He; Weizhu Chen; Tuo Zhao (ICML, 2022)

Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention. - Yichong Xu; Chenguang Zhu 001; Shuohang Wang; Siqi Sun; Hao Cheng 002; Xiaodong Liu 003; Jianfeng Gao 001; Pengcheng He; Michael Zeng 001; Xuedong Huang 001 (IJCAI, 2022)

A Zeroth-Order Block Coordinate Gradient Descent Method For Cellular Network Optimization. - Pengcheng He; Siyuan Lu; Xin Guan; Yibin Kang; Qingjiang Shi (ISWCS, 2022)

A Learned Multi-objective Bacterial Foraging Optimization Algorithm with Continuous Deep Q-Learning. - Tianwei Zhou; Wenwen Zhang; Pengcheng He; Guanghui Yue 001 (ML4CS (3), 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 (NAACL-HLT, 2022)

ALLSH: Active Learning Guided by Local Sensitivity and Hardness. - Shujian Zhang; Chengyue Gong; Xingchao Liu; Pengcheng He; Weizhu Chen; Mingyuan Zhou (NAACL-HLT (Findings), 2022)

MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. - Simiao Zuo; Qingru Zhang; Chen Liang 006; Pengcheng He; Tuo Zhao; Weizhu Chen (NAACL-HLT, 2022)

An Improved Particle Swarm Optimization Algorithm for Irregular Flight Recovery Problem. - Tianwei Zhou; Pengcheng He; Churong Zhang; Yichen Lai; Huifen Zhong; Xusheng Wu (ICSI (1), 2022)

Reinforced Event-Driven Evolutionary Algorithm Based on Double Deep Q-network. - Tianwei Zhou; Wenwen Zhang; Junrui Lu; Pengcheng He; Keqin Yao (ICSI (1), 2022)

Experiences and Lessons Learned From DR Resources Participating in the US and UK Capacity Markets: Mechanisms, Status, Dilemmas and Recommendations. - Jin Sun; Jing Liu; Hao Chen; Pengcheng He; Huihong Yuan; Ze Yan (IEEE Access, 2022)

Mixing and Shifting: Exploiting Global and Local Dependencies in Vision MLPs. - Huangjie Zheng; Pengcheng He; Weizhu Chen; Mingyuan Zhou (CoRR, 2022)

Truncated Diffusion Probabilistic Models. - Huangjie Zheng; Pengcheng He; Weizhu Chen; Mingyuan Zhou (CoRR, 2022)

GODEL: Large-Scale Pre-Training for Goal-Directed Dialog. - Baolin Peng; Michel Galley; Pengcheng He; Chris Brockett; Lars Liden; Elnaz Nouri; Zhou Yu 005; Bill Dolan; Jianfeng Gao 001 (CoRR, 2022)

Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarization. - Pengcheng He; Baolin Peng; Liyang Lu; Song Wang 012; Jie Mei; Yang Liu 124; Ruochen Xu; Hany Hassan Awadalla; Yu Shi 001; Chenguang Zhu 001; Wayne Xiong; Michael Zeng 001; et al. (CoRR, 2022)

Momentum Calibration for Text Generation. - Xingxing Zhang 002; Yiran Liu; Xun Wang 012; Pengcheng He; Yang Yu; Si-Qing Chen; Wayne Xiong; Furu Wei (CoRR, 2022)

Attend to the Right Context: A Plug-and-Play Module for Content-Controllable Summarization. - Wen Xiao; Lesly Miculicich; Yang Liu 124; Pengcheng He; Giuseppe Carenini (CoRR, 2022)

Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarization. - Pengcheng He; Baolin Peng; Song Wang 012; Yang Liu 124; Ruochen Xu; Hany Hassan; Yu Shi 001; Chenguang Zhu 001; Wayne Xiong; Michael Zeng 001; Jianfeng Gao 001; Xuedong Huang 001 (ACL (1), 2023)

DIONYSUS: A Pre-trained Model for Low-Resource Dialogue Summarization. - Yu Li 013; Baolin Peng; Pengcheng He; Michel Galley; Zhou Yu 005; Jianfeng Gao 001 (ACL (1), 2023)

Query Rewriting in Retrieval-Augmented Large Language Models. - Xinbei Ma; Yeyun Gong; Pengcheng He; Hai Zhao 001; Nan Duan (EMNLP, 2023)

LMGQS: A Large-scale Dataset for Query-focused Summarization. - Ruochen Xu; Song Wang 012; Yang Liu 124; Shuohang Wang; Yichong Xu; Dan Iter; Pengcheng He; Chenguang Zhu 001; Michael Zeng 001 (EMNLP (Findings), 2023)

DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing. - Pengcheng He; Jianfeng Gao 001; Weizhu Chen (ICLR, 2023)

Diffusion-GAN: Training GANs with Diffusion. - Zhendong Wang; Huangjie Zheng; Pengcheng He; Weizhu Chen; Mingyuan Zhou (ICLR, 2023)

Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. - Qingru Zhang; Minshuo Chen; Alexander Bukharin; Pengcheng He; Yu Cheng 001; Weizhu Chen; Tuo Zhao (ICLR, 2023)

Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders. - Huangjie Zheng; Pengcheng He; Weizhu Chen; Mingyuan Zhou (ICLR, 2023)

LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation. - Yixiao Li; Yifan Yu 008; Qingru Zhang; Chen Liang 006; Pengcheng He; Weizhu Chen; Tuo Zhao (ICML, 2023)

Less is More: Task-aware Layer-wise Distillation for Language Model Compression. - Chen Liang 006; Simiao Zuo; Qingru Zhang; Pengcheng He; Weizhu Chen; Tuo Zhao (ICML, 2023)

HyperTuning: Toward Adapting Large Language Models without Back-propagation. - Jason Phang; Yi Mao; Pengcheng He; Weizhu Chen (ICML, 2023)

POUF: Prompt-Oriented Unsupervised Fine-tuning for Large Pre-trained Models. - Korawat Tanwisuth; Shujian Zhang; Huangjie Zheng; Pengcheng He; Mingyuan Zhou (ICML, 2023)

Guiding Large Language Models via Directional Stimulus Prompting. - Zekun Li 008; Baolin Peng; Pengcheng He; Michel Galley; Jianfeng Gao 001; Xifeng Yan (NeurIPS, 2023)

In-Context Learning Unlocked for Diffusion Models. - Zhendong Wang; Yifan Jiang 001; Yadong Lu; Yelong Shen; Pengcheng He; Weizhu Chen; Zhangyang (Atlas) Wang; Mingyuan Zhou (NeurIPS, 2023)

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models. - Zhendong Wang; Yifan Jiang 001; Huangjie Zheng; Peihao Wang; Pengcheng He; Zhangyang Wang; Weizhu Chen; Mingyuan Zhou (NeurIPS, 2023)

Cellular Network Optimization Using Unfolding-Based Graph Neural Networks. - Pengcheng He; Yijia Tang; Fan Xu 001; Qingjiang Shi (SPAWC, 2023)

A Prototype-Oriented Clustering for Domain Shift with Source Privacy. - Korawat Tanwisuth; Shujian Zhang; Pengcheng He; Mingyuan Zhou (CoRR, 2023)

Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback. - Baolin Peng; Michel Galley; Pengcheng He; Hao Cheng 002; Yujia Xie; Yu Hu; Qiuyuan Huang; Lars Liden; Zhou Yu 005; Weizhu Chen; Jianfeng Gao 001 (CoRR, 2023)

Instruction Tuning with GPT-4. - Baolin Peng; Chunyuan Li; Pengcheng He; Michel Galley; Jianfeng Gao 001 (CoRR, 2023)

ChatGPT-steered Editing Instructor for Customization of Abstractive Summarization. - Wen Xiao; Yujia Xie; Giuseppe Carenini; Pengcheng He (CoRR, 2023)

Summarization with Precise Length Control. - Lesly Miculicich; Yujia Xie; Song Wang; Pengcheng He (CoRR, 2023)

Interactive Editing for Text Summarization. - Yujia Xie; Xun Wang 012; Si-Qing Chen; Wayne Xiong; Pengcheng He (CoRR, 2023)

Do you really follow me? Adversarial Instructions for Evaluating the Robustness of Large Language Models. - Zekun Li 008; Baolin Peng; Pengcheng He; Xifeng Yan (CoRR, 2023)

Deep Reinforcement Learning from Hierarchical Weak Preference Feedback. - Alexander Bukharin; Yixiao Li; Pengcheng He; Weizhu Chen; Tuo Zhao (CoRR, 2023)

A novel competitive constrained dual-archive dual-stage evolutionary algorithm for constrained multiobjective optimization. - Tianwei Zhou; Pengcheng He; Ben Niu 002; Guanghui Yue 001; Hong Wang 016 (Swarm Evol. Comput., 2023)

PROM: A Phrase-level Copying Mechanism with Pre-training for Abstractive Summarization. - Xinbei Ma; Yeyun Gong; Pengcheng He; Hai Zhao 001; Nan Duan (LREC/COLING, 2024)

Personalized Abstractive Summarization by Tri-agent Generation Pipeline. - Wen Xiao; Yujia Xie; Giuseppe Carenini; Pengcheng He (EACL (Findings), 2024)

Evaluating the Instruction-Following Robustness of Large Language Models to Prompt Injection. - Zekun Li 008; Baolin Peng; Pengcheng He; Xifeng Yan (EMNLP, 2024)

Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective. - Ming Zhong 005; Chenxin An; Weizhu Chen; Jiawei Han 001; Pengcheng He (ICLR, 2024)

DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models. - Yung-Sung Chuang; Yujia Xie; Hongyin Luo; Yoon Kim; James R. Glass; Pengcheng He (ICLR, 2024)

LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models. - Yixiao Li; Yifan Yu 008; Chen Liang 006; Nikos Karampatziakis; Pengcheng He; Weizhu Chen; Tuo Zhao (ICLR, 2024)

Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling. - Huangjie Zheng; Zhendong Wang; Jianbo Yuan; Guanghan Ning; Pengcheng He; Quanzeng You; Hongxia Yang; Mingyuan Zhou (ICLR, 2024)

Switchable Decision: Dynamic Neural Generation Networks. - Shujian Zhang; Korawat Tanwisuth; Chengyue Gong; Pengcheng He; Mingyuan Zhou (ICML, 2024)

Parameter Control Framework for Multiobjective Evolutionary Computation Based on Deep Reinforcement Learning. - Tianwei Zhou; Wenwen Zhang; Ben Niu 002; Pengcheng He; Guanghui Yue 001 (Int. J. Intell. Syst., 2024)

A Parallel Zeroth-Order Framework for Efficient Cellular Network Optimization. - Pengcheng He; Siyuan Lu; Fan Xu 001; Yibin Kang; Qi Yan; Qingjiang Shi (IEEE Trans. Wirel. Commun., 2024)

Boundary-aware adversarial ensemble learning for multivariate time series anomaly detection. - Pengcheng He; Xiaoyang Tan; Yuehua Cheng (Knowl. Based Syst., 2025)

Summaries, Highlights, and Action Items: Design, Implementation and Evaluation of an LLM-powered Meeting Recap System. - Sumit Asthana; Sagih Hilleli; Pengcheng He; Aaron Halfaker (Proc. ACM Hum. Comput. Interact., 2025)

Chain of Draft: Thinking Faster by Writing Less. - Silei Xu; Wenhao Xie; Lingxiao Zhao; Pengcheng He (CoRR, 2025)

Vehealth: pervasive RFID-based driver respiration and heart rate monitoring in driving scenarios. - Xinyan Du; Yifan Li; Hao Guo; Jinyu Luo; Pengcheng He; Jin Cui (Wirel. Networks, 2025)

RL from Teacher-Model Refinement: Gradual Imitation Learning for Machine Translation. - Dongyub Jude Lee; Zhenyi Ye; Pengcheng He (CoRR, 2025)

Optimization-Inspired Graph Neural Network for Cellular Network Optimization. - Pengcheng He; Yijia Tang; Fan Xu 001; Qingjiang Shi (IEEE Trans. Mob. Comput., 2025)