Failure Detection for VLA Models

VLA: Vision-Language-Action

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15 papers1 paper in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

Progress Probes $P^2$ : Lightweight Runtime Monitoring for Vision-Language-Action Models
Oct 22, 2026Atiksh Bhardwaj, Edward W. Duan, Junwon Seo +4Failure Detection for VLA Models Vision-Language-Action Models
Carnegie Mellon University. · Cornell University.
OGAM: Connecting Systematic Testing to Runtime Assurance through Object-Grounded Attention Monitoring for VLA Policies
Oct 5, 2026Haki Darwish, Xiangyu Yin, Changwen Li +3Failure Detection for VLA Models Instruction Generalization in VLA Models
Carl von Ossietzky University of Oldenburg, Germany · Huadian Electric Power Research Institute, China · Institute of Software, Chinese Academy of Science, China +1
VLA-Scope: Shift-Aware Failure Prediction for Vision-Language-Action Models
Sep 18, 2026Kaiwen Zhu, Dongfang Liu, Liangkai LiuFailure Detection for VLA Models Robustness of VLA Models
Department of Computer Science, Texas Tech University, Lubbock, TX, USA · Purdue University, West Lafayette, IN, USA
FailureSpot: Label-Efficient Timestamp-Level Failure Detection for Vision-Language-Action Models
Sep 3, 2026Jie Ma, Zongxi Liu, Yi ZhuFailure Detection for VLA Models Vision-Language-Action Models
Wayne State University
GUARD: Grounding Uncertainty and Ablation-Based Risk Detection for Diffusion-Based VLAs
Aug 5, 2026Suhas Hegde, Jitendra Yasaswi Bharadwaj KattaFailure Detection for VLA Models Uncertainty Estimation for VLA Models
Bosch Research India
SAFECAST: Robust Failure Detection for VLA Policies with Contrast-Set Training and Calibration
Aug 4, 2026Harshitha Rajaprakash, Aditeya Prajapati, Rong Xue +2Failure Detection for VLA Models Vision-Language-Action Models
University of Southern California, Thomas Lord Department of Computer Science
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 Failure Detection for VLA Models
1HKUST(GZ) 2HKUST 3CUHK 4AI² Roboticss
Early Warning Signals for OpenVLA Failure under Visual Distribution Shift
Jun 29, 2026Dipesh Tharu Mahato, Rachel RenRobot Failure Detection Distribution Shift
New York University
VLA-FAIL: Efficient Task Failure Detection for Finetuned Vision-Language-Action Models
Jun 19, 2026Florian Seligmann, Emiliyan Gospodinov, Enes Ulas Dincer +1Failure Detection for VLA Models Mahalanobis Distance
Autonomous Learning Robots Lab, Karlsruhe Institute of Technology · FZI Forschungszentrum Informatik, Karlsruhe
Tri-Info: Generalizable, Interpretable Failure Prediction for VLA Models via Information Theory
Jun 18, 2026Jinghan Yang, Yunchao Zhang, Wang Yuan +4Robot Failure Detection Vision-Language-Action Models
HKU Musketeers Foundation Institute of Data Science · InfoBodied AI Lab, The University of Hong Kong
Perturbation-Based Epistemic Uncertainty for Failure Detection in Vision-Language-Action Models
Jun 18, 2026Yousung Lee, Dongsoo HarFailure Detection for VLA Models Uncertainty Estimation for VLA Models
Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
FATE-VLA:Failue-aware test generation for vision-language-action models
Jun 1, 2026Arusa Kanwal, Pablo Valle, Shaukat Ali +1VLM Evaluation Vision-Language-Action Models
Mondragon University Mondragon, Spain · Simula Research Laboratory Oslo, Norway
Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring
May 29, 2026Seongheon Park, Wendi Li, Changdae Oh +4Robot Failure Detection Fault Detection
University of Wisconsin–Madison · Georgia Institute of Technology
Your Vision-Language-Action Model Already Has Attention Heads For Path Deviation Detection
Mar 14, 2026Jaehwan Jeong, Evelyn Zhu, Jinying Lin +5Robotic Anomaly Detection Failure Detection for VLA Models
Korea University · University of California, Los Angeles · NVIDIA
Act, Think or Abstain: Complexity-Aware Adaptive Inference for Vision-Language-Action Models
Mar 5, 2026Riccardo Andrea Izzo, Gianluca Bardaro, Matteo MatteucciFailure Detection for VLA Models Vision-Language-Action Models
All authors are with the Department of Electronics, Information, and Bioengineering, Politecnico di Milano, Milan, Italy.

Oct 22, 2026J/K move · Enter open · S save

Progress Probes $P^2$ : Lightweight Runtime Monitoring for Vision-Language-Action Models

Atiksh Bhardwaj, Edward W. Duan, Junwon Seo, Prithwish Dan+3

Carnegie Mellon University. · Cornell University.

Failure Detection for VLA Models Vision-Language-Action Models Safety Evaluation of VLA Models

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Vision-Language-Action (VLA) models can perform diverse manipulation tasks directly from visual observations and natural language instructions, but they remain prone to mistakes and unpredictable failures. Deploying these policies without continuous human supervision will require robust runtime monitors that detect when the policy has gone off-course. Existing monitors use external foundation models, such as vision-language models (VLMs) to supervise the policy, introducing significant complexity and computational cost for monitoring at runtime. In this work, we investigate an alternate approach: can a VLA's own internal activations provide the information needed to monitor its execution? Our method trains linear probes on policy activations from demonstrations to estimate progress, then flags executions that deviate from expected progress. In experiments with the open-source VLA

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and across simulated and real-world manipulation tasks, this approach is competitive with or outperforms VLM-based monitors in task failure detection, as well as methods which require failure data for training. These findings suggest that simple probes of VLA internals can be used to develop reliable runtime monitors, opening a path toward building policies that can act reliably and monitor their execution without external foundation models.