Papers by Aaron Xu

2 papers
MemeQA: Holistic Evaluation for Meme Understanding (2025.acl-long)

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Challenge: Existing benchmarks for meme understanding only concern narrow aspects of meme semantics.
Approach: They propose to use multiple-choice questions to evaluate meme comprehension . they use a dataset of over 9,000 multiple-question questions to assess meme comprehension.
Outcome: The proposed model outperforms existing models on meme comprehension . the model makes many errors on memes where proper understanding requires going beyond sentiment .
Memory-QA: Answering Recall Questions Based on Multimodal Memories (2025.emnlp-main)

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Challenge: Memory-QA is a real-world task that involves answering recall questions about visual content from previously stored multimodal memories.
Approach: They propose a memory-QA task that involves answering recall questions about visual content from previously stored multimodal memories.
Outcome: The proposed solution improves memory recording, compression, storage, and search accuracy over state-of-the-art solutions.

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