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This arXiv preprint finds that vision-language-action robot models often ignore "how-level" instructions, such as manner or style cues, and that these instructions can even reduce task success. The authors show that segment-level instruction enrichment improves responsiveness but doesn't reliably generalize to harder or out-of-distribution cases, and they introduce SIMPLER-IN as a new benchmark. For AI readers, the takeaway is that instruction-following in embodied models is still an open problem, and claims based on standard benchmarks may overstate it.
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Do VLAs Really Follow Instructions? Diagnosing How-Level Instruction Following in Vision-Language-Action Models

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arXiv:2610.21251v1 Announce Type: cross Abstract: Vision-language-action (VLA) models are expected to follow instructions like their language backbones, yet prior work has focused on What-level instructions that specify the task rather than How-level instructions that specify how to carry it out. Through our diagnoses, we find that How-level instructions do not help current VLAs and lower task success. We hypothesize that pairing each training episode with a single instruction limits How-level instruction following, and show that training with segment-level enriched instructions makes actions respond to such instructions without consistently raising task success. To measure How-level instruction following beyond standard benchmarks, we introduce SIMPLER-IN, where success requires conditions given only in the instruction. It shows that the gained responsiveness does not extend to demanding or out-of-distribution How-level instructions. How-level instruction following thus remains an open challenge.

Title:Do VLAs Really Follow Instructions? Diagnosing How-Level Instruction Following in Vision-Language-Action Models

Abstract:Vision-language-action (VLA) models are expected to follow instructions like their language backbones, yet prior work has focused on What-level instructions that specify the task rather than How-level instructions that specify how to carry it out. Through our diagnoses, we find that How-level instructions do not help current VLAs and lower task success. We hypothesize that pairing each training episode with a single instruction limits How-level instruction following, and show that training with segment-level enriched instructions makes actions respond to such instructions without consistently raising task success. To measure How-level instruction following beyond standard benchmarks, we introduce SIMPLER-IN, where success requires conditions given only in the instruction. It shows that the gained responsiveness does not extend to demanding or out-of-distribution How-level instructions. How-level instruction following thus remains an open challenge.

Computer Vision and Pattern Recognition (cs.CV); Robotics (cs.RO)

arXiv:2610.21251 [cs.CV]

(or arXiv:2610.21251v1 [cs.CV] for this version)

https://doi.org/10.48550/arXiv.2610.21251 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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