Beck Labash

Artificial Intelligence · 2023

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 41 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it
• Reinforcement Learning — 11 citations into it

Whom Beck Labash trusts overall

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

1. Wenlong Huang
2. Shunyu Yao
3. Mohit Shridhar
4. Yoshua Bengio
5. Geoffrey E. Hinton
6. Zihao Wang
7. Diederik P. Kingma

Who trusts Beck Labash overall

1. Geunwoo Kim
2. Xingyao Wang
3. Guanzhi Wang
4. Shishir G. Patil
5. Yilun Du
6. Zhaorun Chen
7. Zhibin Gou
8. Chengrun Yang
9. Yuxi Xie

Papers from Beck Labash's perspective

Ordered by how strongly the researchers Beck Labash 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. Attention is All you Need (Neural Information Processing Systems)
3. ImageNet classification with deep convolutional neural networks
4. Language Models are Few-Shot Learners (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Gradient-based learning applied to document recognition
9. ImageNet: A large-scale hierarchical image database
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Reflexion: language agents with verbal reinforcement learning (2023) — 4,400 citations
• Reflexion: an autonomous agent with dynamic memory and self-reflection (2023) — 338 citations