Papers by Zhen-Ru Zhang

2 papers
CMMaTH: A Chinese Multi-modal Math Skill Evaluation Benchmark for Foundation Models (2025.coling-main)

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Challenge: Large language models excel in various language tasks, while large multimodal models effectively handle visual-language problems.
Approach: They propose to use a multimodal multimodal model evaluation benchmark to evaluate model performance in Chinese K12 classrooms.
Outcome: The proposed model evaluation tool is integrated with the CMMaTH dataset.
Towards Adaptive Prefix Tuning for Parameter-Efficient Language Model Fine-tuning (2023.acl-short)

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Challenge: Parameter-efficient fine-tuning only optimizes a few task-specific parameters with frozen pre-trained model.
Approach: They propose to optimize a prefix vector inserted into Transformer layers to optimize the prefix . they propose to use a gate mechanism to adjust the prefixed to each layer .
Outcome: The proposed approach improves on the SuperGLUE and NER datasets.

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