AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning

Name: AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
Uploaded: 2026-09-04T20:36:47.606907+00:00
Duration: 222 s
Description: The episode discusses the paper "AIRL-S," which unifies Reinforcement Learning (RL) and search methods for improving Large Language Model (LLM) reasoning. The framework uses Adversarial Inverse Reinforcement Learning (AIRL) to create a robust, generalized Process Reward Model (PRM), achieving significant performance improvements across various reasoning tasks.

The episode discusses the paper "AIRL-S," which unifies Reinforcement Learning (RL) and search methods for improving Large Language Model (LLM) reasoning. The framework uses Adversarial Inverse Reinforcement Learning (AIRL) to create a robust, generalized Process Reward Model (PRM), achieving significant performance improvements across various reasoning tasks.

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