Google DeepMind Researchers Introduce InfAlign: A Machine Learning Framework for Inference-Aware Language Model Alignment

Generative language models often face performance challenges when transitioning from training to real-world applications. A critical issue lies in the misalignment between training objectives and inference-time strategies, such as Best-of-N sampling and controlled decoding. To address this, Google DeepMind and Google Research have introduced InfAlign, a novel machine learning framework designed to enhance language model alignment by incorporating inference-aware methods during the training phase. This development seeks to optimize model performance at inference, ensuring outputs are reliable, high-quality, and consistent across different scenarios.