Xuancheng Ren

Artificial Intelligence · 2017–2023

A researcher in the Science corpus: 11 papers; trusts 482 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 291 citations into it; #35,073 of 35,345 by trust here, #5,788 by citations
• Computer Vision and Pattern Recognition — 175 citations into it; #21,456 of 21,575 by trust here, #10,010 by citations
• Natural Language Processing — 129 citations into it
• Large Language Models — 58 citations into it
• Model Architectures — 55 citations into it
• Evaluation & Benchmarks — 41 citations into it
• Optimization & Training — 39 citations into it
• Multimodal Learning — 38 citations into it

Whom Xuancheng Ren trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Kaiming He
4. Diederik P. Kingma
5. Alex Krizhevsky
6. Ilya Sutskever
7. Yann LeCun
8. Ronald J. Williams
9. Jimmy Ba
10. Oriol Vinyals

Who trusts Xuancheng Ren overall

1. Elias Frantar
2. Serra Sinem Tekiroğlu
3. Xiaohong Huang
4. Lukas Hedegaard

Papers from Xuancheng Ren's perspective

Ordered by how strongly the researchers Xuancheng Ren trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Diversity-Promoting GAN: A Cross-Entropy Based Generative Adversarial Network for Diversified Text Generation (2018) — 152 citations
• Qwen Technical Report (2023) — 4,095 citations
• Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach (2018) — 215 citations
• Aligning Visual Regions and Textual Concepts for Semantic-Grounded Image Representations (2019) — 96 citations
• meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting (2017) — 171 citations
• Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption (2020) — 47 citations
• Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models (2021) — 181 citations
• Hierarchical Inductive Transfer for Continual Dialogue Learning (2022) — 5 citations
• Rethinking Skip Connection with Layer Normalization (2020) — 85 citations
• Aligning Visual Regions and Textual Concepts: Learning Fine-Grained Image Representations for Image Captioning (2019) — 5 citations
• DP-GAN: Diversity-Promoting Generative Adversarial Network for Generating Informative and Diversified Text (2018) — 70 citations