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Ke Chang

2 accepted papers

2025

McBE: A Multi-task Chinese Bias Evaluation Benchmark for Large Language Models

ACL 2025finding

As large language models (LLMs) are increasingly applied to various NLP tasks, their inherent biases are gradually disclosed. Therefore, measuring biases in LLMs is crucial to mitigate its ethical risks. However, most existing bias evaluation datasets are focus on English andNorth American culture,…

Cited by 0SourcePDFScholar
2024

Multi-modal Semantic Understanding with Contrastive Cross-modal Feature Alignment

COLING 2024main

Multi-modal semantic understanding requires integrating information from different modalities to extract users’ real intention behind words. Most previous work applies a dual-encoder structure to separately encode image and text, but fails to learn cross-modal feature alignment, making it hard to ac…