This repository contains a Process Reward Model (PRM) introduced in the paper Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards.

MAHALO (Multi-Action-Head ALignment with PRM-guided DecOding) is a unified framework that standardizes PRM training across verifiable and non-verifiable settings for step-level supervision. It performs vectorized multi-objective alignment and enables controllable inference through objective-specific weighting and PRM-guided decoding.

This model is a process-level reward model based on the Qwen2 architecture. It is designed to provide dense, step-level reward signals to align large language models across multiple objectives, including mathematical reasoning, human values, and interactive tutoring.