Papers by Hengxin Gao

1 papers
Error Comparison Optimization for Large Language Models on Aspect-Based Sentiment Analysis (2025.acl-long)

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Challenge: Existing methods for aspect-based sentiment analysis (ABSA) only compare current predictions and labels on each sample, yet fail to perceive and understand its error outputs from different degrees.
Approach: They propose a framework that can perceive and understand the degree of errors by learning from comparative error pairs.
Outcome: The proposed framework exceeds baselines and achieves the desired performance.

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