Hengxin Gao

Error Comparison Optimization for Large Language Models on Aspect-Based Sentiment Analysis

Supervised fine-tuning (SFT) has enabled large language models (LLMs) to exhibit promising performance on various tasks. However, this fine-tuning process only compares current predictions and labels on each sample, yet fails to perceive and understand its error outputs from different degrees, which…