Yizhe Zhang
Artificial Intelligence · with Gao · 2016–2023
A researcher in the Science corpus: 27 papers; trusts 1,164 researchers and is trusted by 45 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 665 citations into it; #4,761 of 35,345 by trust here, #1,628 by citations
- Natural Language Processing — 494 citations into it; #1,420 of 5,688 by trust here, #614 by citations
- Computer Vision and Pattern Recognition — 361 citations into it; #9,247 of 21,575 by trust here, #3,786 by citations
- Generative Models — 163 citations into it; #1,777 of 1,956 by trust here, #949 by citations
- Representation & Self-Supervised Learning — 91 citations into it; #2,976 of 3,145 by trust here, #1,671 by citations
- Model Architectures — 86 citations into it
- Evaluation & Benchmarks — 72 citations into it
- Large Language Models — 67 citations into it; #326 of 799 by trust here, #399 by citations
Whom Yizhe Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Ilya Sutskever
- Yoshua Bengio
- Ronald J. Williams
- Alex Krizhevsky
- Yann LeCun
- Kaiming He
- Alex Graves
- Sepp Hochreiter
Who trusts Yizhe Zhang overall
- Chunyuan Li
- Eric Michael Smith
- Dinghan Shen
- Andrea Madotto
- Zhe Gan
- Shikib Mehri
- Sergey I. Nikolenko
- Jianfeng Gao
- Michel Galley
- Jing Xu
Papers from Yizhe Zhang's perspective
Ordered by how strongly the researchers Yizhe Zhang 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
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- 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
- What Makes Good In-Context Examples for GPT-3? (2021) — 1,798 citations
- DIALOGPT : Large-Scale Generative Pre-training for Conversational Response Generation (2019) — 1,737 citations
- Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization (2018) — 318 citations
- Adversarial Feature Matching for Text Generation (2017) — 363 citations
- Triangle Generative Adversarial Networks (2017) — 142 citations
- Jointly Optimizing Diversity and Relevance in Neural Response Generation (2019) — 83 citations
- Contextualized Perturbation for Textual Adversarial Attack (2020) — 285 citations
- Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation (2016) — 320 citations
- Microsoft Icecaps: An Open-Source Toolkit for Conversation Modeling (2019) — 7 citations
- Deconvolutional Latent-Variable Model for Text Sequence Matching (2017) — 69 citations
- Stabilizing Transformer Training by Preventing Attention Entropy Collapse (2023) — 184 citations
- Deconvolutional Paragraph Representation Learning (2017) — 79 citations
- A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation (2021) — 203 citations
- JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets (2018) — 44 citations
- Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space (2020) — 202 citations
- Automatic Document Sketching: Generating Drafts from Analogous Texts (2021) — 7 citations
- A Controllable Model of Grounded Response Generation (2020) — 89 citations
- Joint Embedding of Words and Labels for Text Classification (2018) — 428 citations
- Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms (2018) — 351 citations
- Complementary Auxiliary Classifiers for Label-Conditional Text Generation (2020) — 23 citations