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Ranjay Krishna

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#artificial intelligence Preprint Oct 2026

DTDD: Divergence-Triggered Dynamic Distillation for Reliable On-Policy Supervision

On-policy distillation (OPD) provides dense token-level supervision on student rollouts, but this supervision can become unreliable when the student and teacher diverge, either because of a large initial policy gap or compounding errors in long-horizon reasoning and tool use. We introduce Divergence-Triggered Dynamic D...

Qi-Jia He, Ze-Qun Li, Spencer Luo et al. · 0 citations
Preprint Sep 2026

Grounded Action Model: 3D Grounding as a Foundation for Robotics

Manipulation policies must know which objects matter and where they are, yet the pretrained backbones that current robot foundation models build on, from language in vision-language-action models (VLAs) to video generation in world-action models (WAMs), do not directly require this metric grounding, leaving it to be le...

Ge-Hao Zhang, Weikai Huang, S. Shailesh et al. · 0 citations

vla-eval: A Unified Evaluation Harness for Vision-Language-Action Models

Vision-Language-Action (VLA) models are increasingly evaluated across multiple simulation benchmarks, yet adding each benchmark to an evaluation pipeline requires resolving incompatible dependencies, matching underspecified evaluation protocols, and reverse-engineering undocumented preprocessing. This burden scales wit...

Suhwan Choi, YUN-OO Lee, Yubeen Park et al. · 8 citations
Preprint Jul 2026

HumanCLAW: Can Vision-Language Models Act Through a Body?

This work introduces HumanCLAW, an evaluation framework that decouples action decision-making from low-level execution in a vision-language model (VLM), and builds HumanCLAW-Bench, a database of 1,218 long-horizon, egocentric find-navigate-interact episodes across 41 indoor scenes.

Siyao Li, Jiawei Gu, Shuai Liu et al. · 1 citation

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