Uncertainty Estimation for VLA Models

VLA: Vision-Language-Action

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5 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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Triggering Generalist Reasoning via Predictive Uncertainty for Dual-System VLA
Oct 4, 2026Hyemin Yang, Wooseong Jeong, Giwon Lee +1Uncertainty Estimation for VLA Models Efficient VLA Model Inference
KAIST
Do Not Cut When Uncertain: Rejectable and Calibrated Decision Heads for VLA Policies in Robotic Harvesting
Sep 28, 2026Heng ZhangUncertainty Estimation for VLA Models Selective Prediction
Capability-Aware Arbitration for Semantic Intent-Based Shared Control
Sep 21, 2026Zhaoda Du, Michael Bowman, Xiaoli ZhangUncertainty Estimation for VLA Models Human-Robot Collaboration
Colorado School of Mines, Golden, CO 80401, USA. · University of Pennsylvania, Philadelphia, PA 19104, USA.
UDAV: Uncertainty-Driven Adaptive VLM Waypoint Planner
Sep 14, 2026Ghazal Farhani, Shabnam ShabaniUncertainty Estimation for VLA Models Trajectory Generation
The authors are with the Automotive and Surface Transportation Research Centre, National Research Council Canada, London, Ontario, Canada.
Estimating Semantic Ambiguity via Gaussian Context Distributions for VLM-Driven Traversability Analysis
Sep 8, 2026Ramona Häuselmann, Mario A. V. Saucedo, Christoforos Kanellakis +1Uncertainty Estimation for VLA Models Embodied Navigation
Robotics & AI Team, Department of Computer, Electrical and Space Engineering, Luleå University of Technology, Luleå SE-97187, Sweden.
LM-X: Explainable Vision--Language--Action Modeling via Progress, Event, and Uncertainty Prediction
Aug 26, 2026Jin Lou, Zhiyuan Jing, Xupeng Wang +21Robotic Control Uncertainty Estimation for VLA Models
Humanoid Robot (Shanghai) Co., Ltd. · E-surfing Digital Life Technology Co., Ltd., China Telecom
MAE I Trust Myself? Self-Evaluating VLA Action Generation with Markov Attention Entropy
Aug 17, 2026Aniri, Chen Yilin, Jinhe Bi +7Uncertainty Estimation for VLA Models LLM Uncertainty Estimation
Ludwig Maximilian University of Munich · Munich Center for Machine Learning · East China University of Science and Technology +2
GUARD: Grounding Uncertainty and Ablation-Based Risk Detection for Diffusion-Based VLAs
Aug 5, 2026Suhas Hegde, Jitendra Yasaswi Bharadwaj KattaUncertainty Estimation for VLA Models Vision-Language Grounding
Bosch Research India
The Geometry of Flow-Matching Uncertainty: A Cost-free Uncertainty Proxy and Its Application in Flow-based VLA Failure Detection
Jul 30, 2026Ziyang Rao, Yiren Zhao, Weiyu Guo +3Flow Matching Uncertainty Estimation for VLA Models
1HKUST(GZ) 2HKUST 3CUHK 4AI² Roboticss
SUREFlow: State-space Uncertainty-aware REsidual Flow Matching for Robust Robot Manipulation
Jul 11, 2026Md Tanvir Islam, Sai Navaneet Peddapalli, Sangmoon Lee +1Flow Matching Uncertainty Estimation for VLA Models
School of Electronic and Electrical Engineering, Kyungpook National University, Daegu 41566, Republic of Korea
When Thinking Hurts: Epistemic Signals in the Reasoning Chains of Visual Language Models
Jul 9, 2026Mayank SingalVLM Evaluation Uncertainty Estimation for VLA Models
Independent Researcher.
Visual Semantic Entropy: Do Vision Language Models Recognize Visual Ambiguity?
Jun 30, 2026Ta Duc Huy, Trang Nguyen, Townim Chowdhury +5VLM Evaluation Visual Question Answering
Australian Institute for Machine Learning, Adelaide University, Australia · Flinders University, Australia
GroundControl: Anticipating Navigation Failures in Vision-Language Agents via Trajectory-Consistent Uncertainty Estimates
Jun 18, 2026Nastaran Darabi, Divake Kumar, Sina Tayebati +2Uncertainty Estimation for VLA Models Selective Prediction
University of Illinois at Chicago (UIC)
Perturbation-Based Epistemic Uncertainty for Failure Detection in Vision-Language-Action Models
Jun 18, 2026Yousung Lee, Dongsoo HarUncertainty Estimation for VLA Models Robotic Manipulation
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
Uncertainty Quantification for Flow-Based Vision-Language-Action Models
Jun 16, 2026Ralf Römer, Maximilian Seeliger, Saida Liu +5Flow Matching Uncertainty Estimation for VLA Models
TU Munich · ETH Zurich · TU of Munich +1
FUSE: Quantifying Uncertainty in Vision-Language Models by Bayesian Fusing Epistemic and Aleatoric Uncertainty
Jun 1, 2026Harry Zhang, Luca CarloneUncertainty Estimation for VLA Models Vision-Language Models
Massachusetts Institute of Technology
Seeing Isn't Knowing: Do VLMs Know When Not to Answer Spatial Questions (and Why)?
May 28, 2026Yue Zhang, Zun Wang, Han Lin +3VLM Evaluation Spatial Reasoning Benchmarks
UNC Chapel Hill · Google Research
VLAConf: Calibrated Task-Success Confidence for Vision-Language-Action Models
May 28, 2026Dehao Huang, Aoxiang Gu, Chengjie Zhang +5Uncertainty Estimation for VLA Models Probability Calibration
Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China. · Zhongguancun Academy, Beijing, China · National Cybersecurity Academy, Wuhan University, Wuhan, China.
Uncertainty-Aware Gaussian Map for Vision-Language Navigation
May 26, 2026Jianzhe Gao, Rui Liu, Yuxuan Xu +6Uncertainty Estimation for VLA Models Vision-Language Navigation
The State Key Lab of Brain-Machine Intelligence, Zhejiang University · Department of Foundation model, 2012 Labs, Huawei · Noah’s Ark Lab, 2012 Labs, Huawei +1
Look-Closer-Then-Diagnose: Confidence-Aware Ultrasound VQA via Active Zooming
May 20, 2026Yue Zhou, Erxuan Wu, Yikang Sun +5Visual Question Answering Uncertainty Estimation for VLA Models
Computer Aided Medical Procedures (CAMP), TU Munich, Germany · Munich Center for Machine Learning (MCML), Munich, Germany · Zhongshan Hospital, Fudan University, China +1
VISOR: A Vision-Language Model-based Test Oracle for Testing Robots
May 11, 2026Prasun Saurabh, Pablo Valle, Aitor Arrieta +2Uncertainty Estimation for VLA Models Automated Software Testing
Simula Research Laboratory and Oslo Metropolitan University · Mondragon University · National Institute of Informatics
Temporal Difference Calibration in Sequential Tasks: Application to Vision-Language-Action Models
Apr 22, 2026Shelly Francis-Meretzki, Mirco Mutti, Yaniv Romano +1Uncertainty Estimation for VLA Models Vision-Language-Action Models
1Technion - Israel Institute of Technology.
ReconVLA: An Uncertainty-Guided and Failure-Aware Vision-Language-Action Framework for Robotic Control
Apr 17, 2026Lingling Chen, Zongyao Lyu, William J. BeksiUncertainty Estimation for VLA Models Robot Failure Detection
Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, USA
Transport Discrepancy as a Reliability Signal for Vision-Language-Action Models
Dec 1, 2025Wanpeng Zhang, Ye Wang, Hao Luo +6Uncertainty Estimation for VLA Models Vision-Language-Action Models
1Peking University · 3BeingBeyond · 2Renmin University of China

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Triggering Generalist Reasoning via Predictive Uncertainty for Dual-System VLA

Hyemin Yang, Wooseong Jeong, Giwon Lee, Kuk-Jin Yoon

KAIST

Uncertainty Estimation for VLA Models Efficient VLA Model Inference Test-Time Adaptation of VLA Models VLMs for Robotics Reasoning for VLA Models

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Dual-system Vision-Language-Action (VLA) models improve real-time robotic control by pairing a slow, reasoning-capable generalist with a fast specialist action expert. However, existing methods invoke the generalist at a fixed frequency, ignoring the fact that decision-making complexity varies throughout a rollout. This static strategy wastes computation in easy phases and can delay renewed reasoning when the scene changes unexpectedly. We propose TUD (Triggering generalist reasoning via predictive Uncertainty for Dual-system VLA), an adaptive inference framework that selectively skips unnecessary generalist calls. TUD measures the cross-step dispersion of action re-predictions at the upcoming chunk slot under the cached generalist context, as a predictive uncertainty signal. This signal captures how much the future action plan shifts as new observations arrive and is computed from forwards the architecture already runs, requiring neither manual phase labels nor an auxiliary uncertainty model. On VLA-Arena, it achieves a higher success rate at matched call budgets than alternative uncertainty baselines while maintaining low wall-clock overhead, and more consistently separates successful from failed rollouts. Also, TUD finds a more favorable cost-success trade-off than non-adaptive baselines, tracing an entire operating curve as a single threshold is varied, and substantially reduces VLM calls at matched success rate. The same trade-off appears in our real-robot experiments, where TUD cuts generalist calls by 75% relative to the strongest fixed-interval baseline while achieving an even higher success rate. Our results suggest that predictive uncertainty provides a practical criterion for adaptive reasoning in efficient VLA control.

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