AMAP-ML / Tree-GRPO
[ICLR 2026] Tree Search for LLM Agent Reinforcement Learning
Why this job: works in the areas we cover, but does not say which job it does
What it does
We propose Tree-GRPO, adopting a tree-search rollout strategy in place of independent chain-based rollouts for LLM agent RL. Based on ReAct step-level nodes, Tree-GRPO carries out rollout sampling over a semantically well-defined search tree. The Tree-GRPO brings two major advantages: (i) Less rollout budget, (ii) Tree-based process supervion signal.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Inactive
- Last commit 9 months ago
- Stars
- 410
- On GitHub
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 98% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 40% closed
- 3 still open
- Pull requests
- 0 merged
- 0 waiting
- Releases
- None
- Never published
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Python 98%
- Shell 2%
Topics
- agent
- llm
- reinforcement-learning
- tree
- large-language-model
Project record
- JobOther AI tools
- StatusListed
- Commits8
- Forks41
- Watching11
- Stars in 28 days+6
- CreatedSep 25, 2025
- First seen by usNov 7, 2026
- CheckedNov 8, 2026