Min Gao

This work proposes Test-Time Adaptation via Stability-Aware Confidence Optimization (TASCO), a framework that incorporates local stability into confidence-based test-time adaptation while keeping the LLM frozen and improves reasoning accuracy and token efficiency across diverse LLMs and reasoning benchmarks.

Personalized communication skills can transform agentic recommender systems, leading to significant improvements in recommendation accuracy by leveraging diverse user insights.