xxzcc / Awesome-Credit-Assignment-in-LLM-RL
Curated papers, taxonomy, benchmarks, and decision guides for credit assignment in reasoning and agentic LLM reinforcement learning.
Why this job: name: awesome; topics: awesome-list, awesome
What it does
Long-horizon LLM reasoning and agents often learn from sparse outcome rewards. Which token, step, turn, action, or agent deserves the credit?
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 47 days ago
- Stars
- 226
- +2 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 100% closed
- 0 still open
- Pull requests
- 2 merged
- 1 waiting
- Releases
- None
- Never published
- Contributing guide (opens in new tab)
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Python 100%
Topics
- agentic-rl
- awesome
- awesome-list
- credit-assignment
- large-language-models
- llm
- multi-agent-systems
- process-reward-model
- reinforcement-learning
- rlvr
Project record
- JobLists and guides
- StatusListed
- Commits18
- Forks6
- Watching1
- Stars in 28 days+14
- CreatedApr 13, 2026
- First seen by usNov 7, 2026
- CheckedNov 8, 2026