Robert Baruch

Reinforcement Learning · 2022–2025

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

Subfields

• Reinforcement Learning — 32 citations into it

Whom Robert Baruch trusts

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

1. Dean A. Pomerleau (in Reinforcement Learning)
2. Corey Lynch (in Reinforcement Learning)

Papers from Robert Baruch's perspective

Ordered by how strongly the researchers Robert Baruch 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: A large-scale hierarchical image database
4. Multitask Learning
5. Learning Transferable Visual Models From Natural Language Supervision (International Conference on Machine Learning)
6. Grounded Language Learning in a Simulated 3D World
7. Deep Reinforcement Learning from Human Preferences (Neural Information Processing Systems)
8. Understanding natural language
9. Learning Movement Primitives
10. Asking for Help Using Inverse Semantics

Their papers

• Interactive Language: Talking to Robots in Real Time (2022) — 343 citations
• Gemini Robotics: Bringing AI into the Physical World (2025) — 385 citations