RealFeedApp RL Judge improves models' reasoning
The study demonstrates that using agentic judges in reinforcement learning enables models to learn efficient reasoning processes, not just correct outcomes, contrasting with traditional methods.
- Field
- training language models
- What they did
- The researcher tested the hypothesis that using agent-based evaluators (RL Judge) during training allows models to learn more from the same set of data.
- Why it matters
- This could be useful because it allows extracting more value from already paid compute resources without increasing training costs.
#reinforcement learning#rl judge#reasoning#agentic#post-training
