The authors first tested whether supplying an MLLM with summaries of spatial coding-agent execution traces improves its internal chain-of-thought reasoning.
Models can absorb spatial reasoning from verified agent traces
SpatialOPSD trains multimodal models on summarized coding-agent traces, then performs spatial tasks without external tools at inference time.
Chinese Tech
Rongxue Li · Meng Yang · Yiru Mao · Yongliang Tao · Lulu Hu · Bin Yang · +3 more
Alibaba Group
Research Digest··2 min read
Li and colleagues investigate whether multimodal large language models can internalize the geometric reasoning performed by tool-using coding agents.
Why this paper
From Alibaba Group
In one line
SpatialOPSD uses on-policy self-distillation from verified coding agent traces to give MLLMs tool-free spatial reasoning, beating SFT and GRPO.
What we could check
- ·No code link found
- ·No weights link found
- ·No dataset link found
- ·No compute details found
- ·No stated limitations found
- ·No benchmark numbers found
Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.
§