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Igor Mordatch

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Papers (20)

  1. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities cs.CL · 2025 · author #1398
  2. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context cs.CL · 2024 · author #1070
  3. Open X-Embodiment: Robotic Learning Datasets and RT-X Models cs.RO · 2023 · author #90
  4. RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control cs.RO · 2023 · author #31
  5. Improving Factuality and Reasoning in Language Models through Multiagent Debate cs.CL · 2023 · author #5
  6. PaLM-E: An Embodied Multimodal Language Model cs.LG · 2023 · author #21
  7. RT-1: Robotics Transformer for Real-World Control at Scale cs.RO · 2022 · author #26
  8. Inner Monologue: Embodied Reasoning through Planning with Language Models cs.RO · 2022 · author #9
  9. Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents cs.MA · 2019 · author #4
  10. Concept Learning with Energy-Based Models cs.AI · 2018 · author #1
  11. Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control cs.LG · 2018 · author #5
  12. Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines cs.LG · 2018 · author #7
  13. Interpretable and Pedagogical Examples cs.AI · 2017 · author #3
  14. Emergent Complexity via Multi-Agent Competition cs.AI · 2017 · author #5
  15. Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments cs.LG · 2017 · author #5
  16. Learning with Opponent-Learning Awareness cs.AI · 2017 · author #6
  17. Emergence of Grounded Compositional Language in Multi-Agent Populations cs.AI · 2017 · author #1
  18. Prediction and Control with Temporal Segment Models cs.LG · 2017 · author #3
  19. A Paradigm for Situated and Goal-Driven Language Learning cs.CL · 2016 · author #2
  20. Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model cs.RO · 2016 · author #3

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