mlsanityData to 14 Oct 2026

The Role of Predictive Uncertainty and Diversity in Embodied AI and Robot Learning

arXiv 2405.03164 ↗First posted 6 May 2024cs.RO cs.AI cs.CVcited by 11

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Abstract (arXiv)

Uncertainty has long been a critical area of study in robotics, particularly when robots are equipped with analytical models. As we move towards the widespread use of deep neural networks in robots, which have demonstrated remarkable performance in research settings, understanding the nuances of uncertainty becomes crucial for their real-world deployment. This guide offers an overview of the importance of uncertainty and provides methods to quantify and evaluate it from an applications perspective.

Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 77 of its 156 references that are in the map. First posted on arXiv 6 May 2024.

Builds on

77 of 156 references.

References · 77

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
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  3. 2015Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learningcited by 4,448
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  9. 2021A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantificationcited by 792
  10. 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 775
  11. 2018Evidential Deep Learning to Quantify Classification Uncertaintycited by 732
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38 more
  1. 2021Habitat 2.0: Training Home Assistants to Rearrange their Habitatcited by 511
  2. 2016Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithmcited by 507
  3. 2019Measuring Calibration in Deep Learningcited by 446
  4. 2015Deep Kernel Learningcited by 445
  5. 2019Deep Evidential Regressioncited by 355
  6. 2022Conformal prediction beyond exchangeabilitycited by 355
  7. 2023Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Drivingcited by 332
  8. 2023Robots That Ask For Help: Uncertainty Alignment for Large Language Model Plannerscited by 308
  9. 2016Unsupervised Learning for Physical Interaction through Video Predictioncited by 260
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  12. 2015Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP)cited by 177
  13. 2020Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Countscited by 164
  14. 2018Evaluating Bayesian Deep Learning Methods for Semantic Segmentationcited by 143
  15. 2024Language Models with Conformal Factuality Guaranteescited by 131
  16. 2021Epistemic Neural Networkscited by 120
  17. 2022Safe Planning in Dynamic Environments using Conformal Predictioncited by 119
  18. 2020A Review and Comparative Study on Probabilistic Object Detection in Autonomous Drivingcited by 115
  19. 2023Bayes' Rays: Uncertainty Quantification for Neural Radiance Fieldscited by 91
  20. 2019BayesSim: adaptive domain randomization via probabilistic inference for robotics simulatorscited by 85
  21. 2021Stochastic Neural Radiance Fields: Quantifying Uncertainty in Implicit 3D Representationscited by 82
  22. 2020Active Preference-Based Gaussian Process Regression for Reward Learningcited by 71
  23. 2023Benchmarks and Algorithms for Offline Preference-Based Reward Learningcited by 56
  24. 2018Deep Directional Statistics: Pose Estimation with Uncertainty Quantificationcited by 45
  25. 2020Modeling Human Driving Behavior through Generative Adversarial Imitation Learningcited by 45
  26. 2018Time-Agnostic Prediction: Predicting Predictable Video Framescited by 37
  27. 2020Out-of-Distribution Detection for Automotive Perceptioncited by 37
  28. 2018PORCA: Modeling and Planning for Autonomous Driving among Many Pedestrianscited by 36
  29. 2018Learning a Prior over Intent via Meta-Inverse Reinforcement Learningcited by 36
  30. 2019Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensemblescited by 30
  31. 2023pyribs: A Bare-Bones Python Library for Quality Diversity Optimizationcited by 30
  32. 2022Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learningcited by 27
  33. 2023Choose Your Simulator Wisely: A Review on Open-source Simulators for Autonomous Drivingcited by 26
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  35. 2019Dynamic Environment Prediction in Urban Scenes using Recurrent Representation Learningcited by 18
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  38. 2024Probabilistically Correct Language-based Multi-Robot Planning using Conformal Predictioncited by 18

50 most cited of 77 All 77 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 6; 2025: 2; 2026: 3.

11 papers.

  1. 2024Failures Are Fated, But Can Be Faded: Characterizing and Mitigating Unwanted Behaviors in Large-Scale Vision and Language Modelscited by 11
  2. 2024RoboMD: Uncovering Robot Vulnerabilities through Semantic Potential Fieldscited by 7
  3. 2024Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks' Internal Representationscited by 3
  4. 2024Fairness in Autonomous Driving: Towards Understanding Confounding Factors in Object Detection under Challenging Weathercited by 2
  5. 20243D Foundation Models Enable Simultaneous Geometry and Pose Estimation of Grasped Objectscited by 2
  6. 2025Joint Flow Trajectory Optimization For Feasible Robot Motion Generation from Video Demonstrationscited by 2
  7. 2026The Anatomy of Uncertainty in LLMscited by 2
  8. 2025Cross-Modal Instructions for Robot Motion Generationcited by 1
  9. 2026The Essence of Balance for Self-Improving Agents in Vision-and-Language Navigationcited by 1
  10. 2024BaTCAVe: Trustworthy Explanations for Robot Behaviorscited by 0
  11. 2026Uncertainty, Vagueness, and Ambiguity in Human-Robot Interaction: Why Conceptualization Matterscited by 0