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Was reading the score-centering RL paper to add some notes on it the my book, and they have a great table in the appendix on the different importance sampling based train-inference mismatch methods in RL. These have been the biggest focus of RL algorithm research since the GRPO takeoff, imo.
- Who
- Nathan Lambert
- What
- highlighted an appendix table of importance sampling based train-inference mismatch methods in RL
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See the full storyNathan Lambert Highlights Importance Sampling Methods for RL Training–Inference MismatchWas reading the score-centering RL paper to add some notes on it the my book, and they have a great table in the appendix on the different importance sampling based train-inference mismatch methods in RL. These have been the biggest focus of RL algorithm research since the GRPO takeoff, imo.
The story so far
Nathan Lambert highlighted an appendix table in the score-centering RL paper that compares importance sampling methods for addressing training–inference mismatch in reinforcement learning. He said he encountered the table while reading the paper to add notes to his book. Lambert described these methods as, in his view, the biggest focus of RL algorithm research since GRPO took off.
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