#differentiable-computing News & Analysis

You Can Learn Tokenization End-to-End with Reinforcement Learning

Researchers propose learning tokenization boundaries in large language models using reinforcement learning and score function estimates instead of hardcoded compression. This approach directly optimizes discrete token boundaries, outperforming prior straight-through estimation methods at the 100 million parameter scale.