Researchers propose Turn-level Multiscale Density Ratio Estimation (tlm-DRE), a training method for Large Language Model (LLM) agents that improves performance on complex multi-turn tasks. The method assigns different weights to turns and trains on token-level gaps across multiple turns. Experiments show competitive results compared to traditional alignment methods.