Papers by Zhixiong Zeng

2 papers
Reasoning with Multimodal Sarcastic Tweets via Modeling Cross-Modality Contrast and Semantic Association (2020.acl-main)

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Challenge: Existing methods for sarcasm detection rely on text data, but are insufficient to detect multimodal sarcasm.
Approach: They propose a method for modeling cross-modality contrast in the associated context by constructing the Decomposition and Relation Network.
Outcome: The proposed model can detect sarcasm in multimodal tweets using a dataset .
Mitigating Training Imbalance in LLM Fine-Tuning via Selective Parameter Merging (2024.emnlp-main)

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Challenge: Existing studies suggest that the order of training samples can affect model performance, but this is not the case.
Approach: They propose to merge supervised fine-tuning models with different data orders to mitigate this imbalance by parameter merging.
Outcome: The proposed method outperforms the weighted-average method on five datasets.

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