Jiaming Ji
Artificial Intelligence · 2023
A researcher in the Science corpus: 4 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 Jiaming Ji trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Eitan Altman
- John Schulman
- Yuntao Bai
- Daniel Martin Katz
- Samuel Gehman
- Takahiro Miki
- Long Ouyang
- Geoffrey E. Hinton
- Ethan Perez
- Diederik P. Kingma
Who trusts Jiaming Ji overall
Papers from Jiaming Ji's perspective
Ordered by how strongly the researchers Jiaming Ji trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Language Models are Few-Shot Learners (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
- AI Alignment: A Comprehensive Survey (2023) — 376 citations
- Baichuan 2: Open Large-scale Language Models (2023) — 1,014 citations