It’s another month in AI research, and it’s hard to pick favorites. This month, I am going over a paper that discusses strategies for the continued pretraining of LLMs, followed by a discussion of reward modeling used in reinforcement learning with human feedback (a popular LLM alignment method), along with a new benchmark. Continued pretraining for LLMs is an important topic because it allows us to update existing LLMs, for instance, ensuring that these models remain up-to-date with the latest information and trends. Also, it allows us to adapt them to new target domains without having them …