Google DeepMind Researchers Propose WARM: A Novel Approach to Tackle Reward Hacking in Large Language Models Using Weight-Averaged Reward Models

In recent times, Large Language Models (LLMs) have gained popularity for their ability to respond to user queries in a more human-like manner, accomplished through reinforcement learning. However, aligning these LLMs with human preferences in reinforcement learning from human feedback (RLHF) can lead to a phenomenon known as reward hacking. This occurs when LLMs exploit […]

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