Thomas Kollar

Artificial Intelligence · Conference on Robot Learning · 2024

A researcher in the Science corpus: 3 papers; trusts 91 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 86 citations into it
• Computer Vision and Pattern Recognition — 86 citations into it
• Evaluation & Benchmarks — 15 citations into it

Whom Thomas Kollar trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Yoshua Bengio
6. Ross B. Girshick
7. Ilya Sutskever
8. Yann LeCun

Papers from Thomas Kollar's perspective

Ordered by how strongly the researchers Thomas Kollar 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Microsoft COCO: Common Objects in Context
7. ImageNet: A large-scale hierarchical image database
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• OpenVLA: An Open-Source Vision-Language-Action Model (2024) — 2,794 citations
• DataComp-LM: In search of the next generation of training sets for language models (2024) — 374 citations
• Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models (2024) — 367 citations