Lichao Sun

Artificial Intelligence · arXiv.org · 2018–2024

A researcher in the Science corpus: 22 papers; trusts 895 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 1,008 citations into it; #9,784 of 35,345 by trust here, #8,706 by citations
• Computer Vision and Pattern Recognition — 362 citations into it
• Natural Language Processing — 253 citations into it
• Safety, Robustness & Interpretability — 156 citations into it
• Privacy & Security — 121 citations into it; #317 of 709 by trust here, #632 by citations
• Large Language Models — 112 citations into it
• Generative Models — 98 citations into it
• Federated & Distributed Learning — 95 citations into it; #103 of 319 by trust here, #305 by citations

Whom Lichao Sun trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Yann LeCun
5. Cynthia Dwork
6. Diederik P. Kingma
7. Kaiming He
8. Ilya Sutskever
9. John C. Duchi
10. Ian J. Goodfellow

Who trusts Lichao Sun overall

1. Lingjuan Lyu
2. Carl Yang
3. Wenke Huang
4. Chaoyang He
5. Zhuangdi Zhu
6. Ke Zhang
7. Mang Ye
8. Xuefei Yin
9. Liang Chen
10. Philip S. Yu

Papers from Lichao Sun's perspective

Ordered by how strongly the researchers Lichao Sun 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A generalist vision–language foundation model for diverse biomedical tasks (2023) — 401 citations
• Adv-BERT: BERT is not robust on misspellings! Generating nature adversarial samples on BERT (2020) — 117 citations
• BadGPT: Exploring Security Vulnerabilities of ChatGPT via Backdoor Attacks to InstructGPT (2023) — 110 citations
• LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy (2020) — 278 citations
• Secure Deep Graph Generation with Link Differential Privacy (2020) — 52 citations
• User Preference-aware Fake News Detection (2021) — 345 citations
• Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models (2024) — 683 citations
• TrustLLM: Trustworthiness in Large Language Models (2024) — 353 citations
• A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT (2023) — 821 citations
• Decentralized Federated Learning: A Survey and Perspective (2023) — 320 citations
• Federated Multi-view Learning for Private Medical Data Integration and Analysis (2021) — 50 citations
• Subgraph Federated Learning with Missing Neighbor Generation (2021) — 297 citations
• Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding (2021) — 72 citations
• Membership Inference Attacks on Machine Learning: A Survey (2021) — 704 citations
• A Survey on Text Classification: From Shallow to Deep Learning (2020) — 173 citations
• Privacy and Robustness in Federated Learning: Attacks and Defenses (2020) — 538 citations
• A Survey on Text Classification: From Traditional to Deep Learning (2020) — 549 citations
• Federated Model Distillation with Noise-Free Differential Privacy (2020) — 133 citations
• Differentially Private Deep Learning with Smooth Sensitivity (2020) — 13 citations
• Private Model Compression via Knowledge Distillation (2018) — 133 citations