Jianfeng Gao24 papers on this site (2011–2024)Large Language Models: A SurveyShervin Minaee, Tomas Mikolov, Narjes Nikzad, et al.2024Chameleon: Plug-and-Play Compositional Reasoning with Large Language ModelsPan Lu, Baolin Peng, Hao Cheng, et al.2023Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated FeedbackBaolin Peng, Michel Galley, Pengcheng He, et al.2023Instruction Tuning with GPT-4Baolin Peng, Chunyuan Li, Pengcheng He, et al.2023LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One DayChunyuan Li, Cliff Wong, Sheng Zhang, et al.2023MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual ContextsPan Lu, Hritik Bansal, Tony Xia, et al.2023Model Tells You What to Discard: Adaptive KV Cache Compression for LLMsSuyu Ge, Yunan Zhang, Liyuan Liu, et al.2023DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding SharingPengcheng He, Jianfeng Gao, Weizhu Chen2021DeBERTa: Decoding-enhanced BERT with Disentangled AttentionPengcheng He, Xiaodong Liu, Jianfeng Gao, et al.2020Generation-Augmented Retrieval for Open-domain Question AnsweringYuning Mao, Pengcheng He, Xiaodong Liu, et al.2020Oscar: Object-Semantics Aligned Pre-training for Vision-Language TasksXiujun Li, Xi Yin, Chunyuan Li, et al.2020SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized OptimizationHaoming Jiang, Pengcheng He, Weizhu Chen, et al.2020UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-TrainingHangbo Bao, Li Dong, Furu Wei, et al.2020DialoGPT: Large-Scale Generative Pre-training for Conversational Response GenerationYizhe Zhang, Siqi Sun, Michel Galley, et al.2019Multi-Task Deep Neural Networks for Natural Language UnderstandingXiaodong Liu, Pengcheng He, Weizhu Chen, et al.2019PIQA: Reasoning about Physical Commonsense in Natural LanguageYonatan Bisk, Rowan Zellers, Ronan Le Bras, et al.2019Unified Language Model Pre-training for Natural Language Understanding and GenerationLi Dong, Nan Yang, Wenhui Wang, et al.2019ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading ComprehensionSheng Zhang, Xiaodong Liu, Jingjing Liu, et al.2018A Diversity-Promoting Objective Function for Neural Conversation ModelsJiwei Li, Michel Galley, Chris Brockett, et al.2016A Persona-Based Neural Conversation ModelJiwei Li, Michel Galley, Chris Brockett, et al.2016Deep Reinforcement Learning for Dialogue GenerationJiwei Li, Will Monroe, Alan Ritter, et al.2016MS MARCO: A Human Generated MAchine Reading COmprehension DatasetPayal Bajaj, Daniel Campos, Nick Craswell, et al.2016A Neural Network Approach to Context-Sensitive Generation of Conversational ResponsesAlessandro Sordoni, Michel Galley, Michael Auli, et al.2015Domain Adaptation via Pseudo In-Domain Data SelectionAmittai Axelrod, Xiaodong He, Jianfeng Gao2011