--- title: "Jianfeng Gao — papers" description: "Jianfeng Gao: 29 papers in the Elamur Research library (2011–2024) — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/authors/jianfeng-gao/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/jianfeng-gao/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Jianfeng Gao # Jianfeng Gao 29 papers on this site (2011–2024) [OpenAlex](https://openalex.org/A5114910293) · [ORCID](https://orcid.org/0000-0002-5702-6143) · h-index 87 · 468 works · 38308 citations (openalex-snapshot, 2026-10-14) Profile data from OpenAlex; authors with the same name are not always told apart. - [Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/minaee-2024-large-language-models-survey/) — Shervin Minaee, Tomas Mikolov, Narjes Nikzad, et al. · 2024 - [Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2023-chameleon-plug-play-compositional-reasoning/) — Pan Lu, Baolin Peng, Hao Cheng, et al. · 2023 - [Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback](https://md.research.elamur.ai/free/en/papers/peng-2023-check-facts-try-again-improving/) — Baolin Peng, Michel Galley, Pengcheng He, et al. · 2023 - [Instruction Tuning with GPT-4](https://md.research.elamur.ai/free/en/papers/peng-2023-instruction-tuning-gpt-4/) — Baolin Peng, Chunyuan Li, Pengcheng He, et al. · 2023 - [LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day](https://md.research.elamur.ai/free/en/papers/li-2023-llava-med-training-large-language/) — Chunyuan Li, Cliff Wong, Sheng Zhang, et al. · 2023 - [MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts](https://md.research.elamur.ai/free/en/papers/lu-2023-mathvista-evaluating-mathematical-reasoning-foundation/) — Pan Lu, Hritik Bansal, Tony Xia, et al. · 2023 - [Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs](https://md.research.elamur.ai/free/en/papers/ge-2023-model-tells-discard-adaptive-kv/) — Suyu Ge, Yunan Zhang, Liyuan Liu, et al. · 2023 - [DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing](https://md.research.elamur.ai/free/en/papers/he-2021-debertav3-improving-deberta-using-electra/) — Pengcheng He, Jianfeng Gao, Weizhu Chen · 2021 - [DeBERTa: Decoding-enhanced BERT with Disentangled Attention](https://md.research.elamur.ai/free/en/papers/he-2020-deberta-decoding-enhanced-bert-disentangled/) — Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al. · 2020 - [Few-shot Natural Language Generation for Task-Oriented Dialog](https://md.research.elamur.ai/free/en/papers/peng-2020-few-shot-natural-language-generation/) — Baolin Peng, Chenguang Zhu, Chunyuan Li, et al. · 2020 - [Generation-Augmented Retrieval for Open-domain Question Answering](https://md.research.elamur.ai/free/en/papers/mao-2020-generation-augmented-retrieval-open-domain/) — Yuning Mao, Pengcheng He, Xiaodong Liu, et al. · 2020 - [MIND: A Large-scale Dataset for News Recommendation](https://md.research.elamur.ai/free/en/papers/wu-2020-mind-large-scale-dataset-news/) — Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, et al. · 2020 - [Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks](https://md.research.elamur.ai/free/en/papers/li-2020-oscar-object-semantics-aligned-pre/) — Xiujun Li, Xi Yin, Chunyuan Li, et al. · 2020 - [SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization](https://md.research.elamur.ai/free/en/papers/jiang-2020-smart-robust-efficient-fine-tuning/) — Haoming Jiang, Pengcheng He, Weizhu Chen, et al. · 2020 - [UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training](https://md.research.elamur.ai/free/en/papers/bao-2020-unilmv2-pseudo-masked-language-models/) — Hangbo Bao, Li Dong, Furu Wei, et al. · 2020 - [DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation](https://md.research.elamur.ai/free/en/papers/zhang-2019-dialogpt-large-scale-generative-pre/) — Yizhe Zhang, Siqi Sun, Michel Galley, et al. · 2019 - [Multi-Task Deep Neural Networks for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/liu-2019-multi-task-deep-neural-networks/) — Xiaodong Liu, Pengcheng He, Weizhu Chen, et al. · 2019 - [PIQA: Reasoning about Physical Commonsense in Natural Language](https://md.research.elamur.ai/free/en/papers/bisk-2019-piqa-reasoning-about-physical-commonsense/) — Yonatan Bisk, Rowan Zellers, Ronan Le Bras, et al. · 2019 - [Unified Language Model Pre-training for Natural Language Understanding and Generation](https://md.research.elamur.ai/free/en/papers/dong-2019-unified-language-model-pre-training/) — Li Dong, Nan Yang, Wenhui Wang, et al. · 2019 - [ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension](https://md.research.elamur.ai/free/en/papers/zhang-2018-record-bridging-gap-between-human/) — Sheng Zhang, Xiaodong Liu, Jingjing Liu, et al. · 2018 - [End-to-End Task-Completion Neural Dialogue Systems](https://md.research.elamur.ai/free/en/papers/li-2017-end-end-task-completion-neural/) — Xiujun Li, Yun-Nung Chen, Lihong Li, et al. · 2017 - [Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access](https://md.research.elamur.ai/free/en/papers/dhingra-2017-end-end-reinforcement-learning-dialogue/) — Bhuwan Dhingra, Lihong Li, Xiujun Li, et al. · 2017 - [A Diversity-Promoting Objective Function for Neural Conversation Models](https://md.research.elamur.ai/free/en/papers/li-2016-diversity-promoting-objective-function-neural/) — Jiwei Li, Michel Galley, Chris Brockett, et al. · 2016 - [A Persona-Based Neural Conversation Model](https://md.research.elamur.ai/free/en/papers/li-2016-persona-based-neural-conversation-model/) — Jiwei Li, Michel Galley, Chris Brockett, et al. · 2016 - [Deep Reinforcement Learning for Dialogue Generation](https://md.research.elamur.ai/free/en/papers/li-2016-deep-reinforcement-learning-dialogue-generation/) — Jiwei Li, Will Monroe, Alan Ritter, et al. · 2016 - [MS MARCO: A Human Generated MAchine Reading COmprehension Dataset](https://md.research.elamur.ai/free/en/papers/bajaj-2016-ms-marco-human-generated/) — Payal Bajaj, Daniel Campos, Nick Craswell, et al. · 2016 - [A Neural Network Approach to Context-Sensitive Generation of Conversational Responses](https://md.research.elamur.ai/free/en/papers/sordoni-2015-neural-network-approach-context-sensitive/) — Alessandro Sordoni, Michel Galley, Michael Auli, et al. · 2015 - [Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval](https://md.research.elamur.ai/free/en/papers/liu-2015-representation-learning-multi-task-deep/) — Xiaodong Liu, Jianfeng Gao, Xiaodong He, et al. · 2015 - [Domain Adaptation via Pseudo In-Domain Data Selection](https://md.research.elamur.ai/free/en/papers/axelrod-2011-domain-adaptation-pseudo-domain-data/) — Amittai Axelrod, Xiaodong He, Jianfeng Gao · 2011