Task Decomposition via VLM Limited by Robot's Own Comprehension
svlevine · x · 2026-07-04
Using a high-level VLM policy to break down complex tasks into steps (a common technique) yields reasonable intermediate steps. However, the VLM still repeatedly instructs the robot to use a hammer, oblivious to what the robot actually understands. This highlights the semantic gap between high-level planning and low-level execution.
More from Research
- Kimi K3 may be strong on cyber, but token efficiency keeps it off UK AISIS — teortaxesTex · 2026-07-27
- ARC AGI 3 should have stayed private, with no examples or public dataset — flowersslop · 2026-07-27
- ExploitGym may have only 60–70% solvable tasks, fueling the OpenAI cheating debate — max_paperclips · 2026-07-27
- Noahpinion quotes Chollet: intelligence may hit a hard ceiling — binarybits · 2026-07-27
- Paper argues graph topology can become the core operating system for AI agents — theomitsa · 2026-07-27
- A question probes how multi-agent branching scales against compute budget and model size — iskander · 2026-07-27