
A reading list worth keeping: LLM4Annotation
A practical post. The GitHub repo LLM4Annotation (Zhen-Tan-dmml/LLM4Annotation) is a curated, updated list of papers and tools at the intersection of LLMs and data annotation. If you work in this
Booth 21-25 | AI Data Management Zone | Tokyo Big Sight

A practical post. The GitHub repo LLM4Annotation (Zhen-Tan-dmml/LLM4Annotation) is a curated, updated list of papers and tools at the intersection of LLMs and data annotation. If you work in this

There’s a quiet result from Cheng et al. (Renmin University and Microsoft Research, 2026) that I keep coming back to. They gave large language models access to a minimal sandbox — essentially a code interpreter with a file system — and watched what happened. No additional training. No new data.
