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Agentic RL: Frameworks and Best Practices

How LLMs are trained to handle long horizon tasks in complex environments...
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Agent Evaluation: A Detailed Guide
Best practices and common patterns for effectively evaluating AI agents...
 • Cameron R. Wolfe, Ph.D.
RL Scaling Laws for LLMs
How scaling laws have evolved from pretraining to reinforcement learning...
 • Cameron R. Wolfe, Ph.D.
The Anatomy of an LLM Benchmark
Common patterns used to create the most effective LLM evaluation datasets...
 • Cameron R. Wolfe, Ph.D.
Applying Statistics to LLM Evaluations
Most LLM evaluations are conducted without a deep consideration of statistics.
 • Cameron R. Wolfe, Ph.D.
Rubric-Based Rewards for RL
Extending the benefits of large-scale RL training to non-verifiable domains...
Continual Learning with RL for LLMs
Exploring the impressive continual learning capabilities of RL training...
 • Cameron R. Wolfe, Ph.D.
GRPO++: Tricks for Making RL Actually Work
How to go from the vanilla GRPO algorithm to functional RL training at scale...
 • Cameron R. Wolfe, Ph.D.
Olmo 3 and the Open LLM Renaissance
Fully-open artifacts with the potential to make LLM research a reality for anyone...
 • Cameron R. Wolfe, Ph.D.
Group Relative Policy Optimization (GRPO)
How the algorithm that teaches LLMs to reason actually works...
 • Cameron R. Wolfe, Ph.D.
Deep (Learning) Focus
Deep (Learning) Focus
I contextualize and explain important topics in AI research.
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