ConflictVLA-Bench: Benchmarking Behavioral Responses of Vision-Language-Action Models to Premise Conflicts

arXiv:2609.31792 · cs.AI, cs.RO · Submitted 2026-09-25 · Read on arXiv

cs.AI, cs.RO

Submitted: 2026-09-25

Updated: 2026-09-25

Code: https://github.com/EmbodiedAISurvey/ConflictVLA-Bench

Terminology

• Grounding — 14× in this paper · explained in 3 episodes
• Benchmark — 11× in this paper · explained in 2 episodes
• Affordance — 7× in this paper · explained in 1 episode
• Trajectory Similarity — 7× in this paper
• Action Magnitude Suppression — 5× in this paper
• Benchmarking — 5× in this paper · explained in 3 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Robustness — 3× in this paper · explained in 5 episodes
• Target Approach Ratio — 3× in this paper
• Abstention — 2× in this paper · explained in 1 episode
• Foundation Model — 2× in this paper · explained in 3 episodes
• Physical Constraints — 2× in this paper · explained in 7 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Vision-Language-Action (VLA) Models — 2× in this paper · explained in 2 episodes
• World Model — 2× in this paper · explained in 7 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Annotation Errors — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• VLA Models — 1× in this paper · explained in 3 episodes
• While Vision-Language-Action — 1× in this paper

Sources

• OpenVLA: An Open-Source Vision-Language-Action Model
• $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
• GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
• RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots
• VLA-Arena: An Open-Source Framework for Benchmarking Vision-Language-Action Models
• Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
• Inner Monologue: Embodied Reasoning through Planning with Language Models
• Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners
• The Yes-Man Syndrome: Benchmarking Abstention in Embodied Robotic Agents
• HazardArena: Evaluating Semantic Safety in Vision-Language-Action Models
• SafeVLA-Bench: A Benchmark for the Success-Safety Gap in Vision-Language-Action Models
• When Vision Overrides Language: Evaluating and Mitigating Counterfactual Failures in VLAs
• Restoring Linguistic Grounding in VLA Models via Train-Free Attention Recalibration
• LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization
• LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models
• VLA-Trace: Diagnosing Vision-Language-Action Models through Representation and Behavior Tracing
• Don't Take the Premise for Granted: Evaluating the Premise Critique Ability of Large Language Models
• FAST: Efficient Action Tokenization for Vision-Language-Action Models
• Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
• $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization

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