Large Language Model

In this work, we revisit entropy–a signal of exploration in RL–and examine its relationship to exploratory reasoning in LMs.

We propose ValuePilot, a two-phase value-driven decision-making framework comprising a dataset generation toolkit DGT and a decision-making module DMM trained on the generated data.

This paper systematically investigates domain adaptation of MLLMs via post-training, focusing on data synthesis, training pipeline, and task evaluation.