Linyi Yang
Artificial Intelligence · 2023
A researcher in the Science corpus: 5 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 277 citations into it
- Evaluation & Benchmarks — 83 citations into it
- Natural Language Processing — 83 citations into it
Whom Linyi Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Alex Krizhevsky
- Ilya Sutskever
- Kaiming He
- Yann LeCun
- Alec Radford
- Ian J. Goodfellow
- Pranav Rajpurkar
Papers from Linyi Yang's perspective
Ordered by how strongly the researchers Linyi Yang trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet classification with deep convolutional neural networks
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Language Models are Few-Shot Learners (Neural Information Processing Systems)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- A Survey on Evaluation of Large Language Models (2023) — 3,582 citations
- PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization (2023) — 400 citations
- On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective (2023) — 310 citations
- Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature (2023) — 365 citations
- PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts (2023) — 312 citations