Papers by Zhongxing Xu

2 papers
MMRC: A Large-Scale Benchmark for Understanding Multimodal Large Language Model in Real-World Conversation (2025.acl-long)

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Challenge: Existing multimodal large language models lack the ability to memorize, recall, and reason in sustained interactions.
Approach: They propose a multimodal real-world conversation benchmark for evaluating open-ended abilities of multimodal large language models.
Outcome: The proposed benchmarks show that the models perform better in open-ended conversations.
PsychEthicsBench: Evaluating Large Language Models Against Australian Mental Health Ethics (2026.findings-acl)

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Challenge: Mental disorders affect nearly one in seven people worldwide, yet the vast majority do not receive adequate care.
Approach: They propose a framework to evaluate LLMs' ethical knowledge and behavioral responses through multiple-choice and open-ended tasks with fine-grained ethicality annotations.
Outcome: Empirical results across 14 models reveal that refusal rates are poor indicators of ethical behavior, revealing a significant divergence between safety triggers and clinical appropriateness.

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