LogSage: Log Summarization Assistant with Guided Enhancement
Yang Lu · 2025
LogSage (Log Summarization Assistant with Guided Enhancement) is a novel system designed to automate the generation of summaries from log data by applying few-shot learning and Reinforcement Learning with Human Feedback (RLHF) techniques. The system's architecture incorporates a three-stage process. Initially, LogSage is trained using pairs of log entries and their corresponding human-written summaries to establish foundational understanding. Then, a base model processes these log entries, extracting essential content for summarization. To ensure the quality of the generated summaries, a reward model evaluates the outputs using expert human feedback. This feedback is instrumental in calibrating the summaries' accuracy and relevancy. Finally, an aligned model refines the summaries based on the reward assessments, producing outputs that closely emulate human-quality text. LogSage represents a significant advancement in log analysis technology, offering precise, scalable, and efficient summarization capabilities that enhance both interpretability and actionable insights from voluminous log data.