A new full-body benchmark shows that current VLMs can recognize targets but cannot reliably tell where their own body is, whether it arrived, or whether it collided; the best solves only 16.8% of episodes.
Llamo: Scaling pretrained language models for unified motion understanding and generation with continuous autoregressive tokens
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
HumanCLAW: Can Vision-Language Models Act Through a Body?
A new full-body benchmark shows that current VLMs can recognize targets but cannot reliably tell where their own body is, whether it arrived, or whether it collided; the best solves only 16.8% of episodes.