Mickel Liu

Artificial Intelligence · 2023

A researcher in the Science corpus: 3 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 117 citations into it
• Large Language Models — 48 citations into it
• Safety, Robustness & Interpretability — 24 citations into it
• Reinforcement Learning — 19 citations into it
• Health Informatics — 10 citations into it

Whom Mickel Liu trusts overall

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

1. Eitan Altman
2. John Schulman

Papers from Mickel Liu's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Layer Normalization
7. Proximal Policy Optimization Algorithms (arXiv.org)
8. Long Short-Term Memory
9. Language Models are Few-Shot Learners (Neural Information Processing Systems)
10. Training language models to follow instructions with human feedback (Neural Information Processing Systems)

Their papers

• Safe RLHF: Safe Reinforcement Learning from Human Feedback (2023) — 750 citations
• BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset (2023) — 964 citations
• Baichuan 2: Open Large-scale Language Models (2023) — 1,014 citations