Xiang Gao
Artificial Intelligence · with Zhang · 2008–2021
A researcher in the Science corpus: 12 papers; trusts 637 researchers and is trusted by 16 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 226 citations into it; #12,132 of 35,345 by trust here, #4,080 by citations
- Natural Language Processing — 179 citations into it; #2,080 of 5,688 by trust here, #966 by citations
- Computer Vision and Pattern Recognition — 134 citations into it; #20,886 of 21,575 by trust here, #7,249 by citations
- Evaluation & Benchmarks — 40 citations into it
- Model Architectures — 32 citations into it
- Large Language Models — 30 citations into it; #325 of 799 by trust here, #399 by citations
- Generative Models — 22 citations into it
- Signal Processing — 20 citations into it
Whom Xiang Gao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Diederik P. Kingma
- Geoffrey E. Hinton
- Ilya Sutskever
- Alex Krizhevsky
- Kyunghyun Cho
- Karen Simonyan
- Kaiming He
- Alex Graves
- Yann LeCun
Who trusts Xiang Gao overall
- Chunyuan Li
- Baolin Peng
- Michel Galley
- Siqi Bao
- Minlie Huang
- Yizhe Zhang
- Eric Michael Smith
- Lianhui Qin
Papers from Xiang Gao's perspective
Ordered by how strongly the researchers Xiang Gao trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- DIALOGPT : Large-Scale Generative Pre-training for Conversational Response Generation (2019) — 1,737 citations
- Conversing by Reading: Contentful Neural Conversation with On-demand Machine Reading (2019) — 111 citations
- Jointly Optimizing Diversity and Relevance in Neural Response Generation (2019) — 83 citations
- Microsoft Icecaps: An Open-Source Toolkit for Conversation Modeling (2019) — 7 citations
- MobileFaceNets: Efficient CNNs for Accurate Real-time Face Verification on Mobile Devices (2018) — 706 citations
- Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space (2020) — 202 citations
- Dialog System Technology Challenge 7 (2019) — 38 citations
- A Controllable Model of Grounded Response Generation (2020) — 89 citations
- NICE: Neural Image Commenting with Empathy (2021) — 9 citations
- Grounded Response Generation Task at DSTC7 (2019)
- Deep reinforcement learning for time series: playing idealized trading games (2018) — 16 citations
- The All-Particle Spectrum of Primary Cosmic Rays in the Wide Energy Range from 1014 to 1017 eV Observed with the Tibet-III Air-Shower Array (2008) — 217 citations