Haoyang Ruan

Textual Self-Attention Network: Test-Time Preference Optimization Through Textual Gradient-Based Attention

Large Language Models (LLMs) have demonstrated remarkable generalization capabilities, but aligning their outputs with human preferences typically requires expensive supervised fine-tuning. Recent test-time methods leverage textual feedback to overcome this, but they often critique and revise a sing