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October 2, 2025Open Access

Beyond Spurious Signals: Debiasing Multimodal Large Language Models via Counterfactual Inference and Adaptive Expert Routing

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This framework improves robustness and generalization in multimodal tasks, indicating better performance than unimodal strategies.

The proposed framework significantly improves robustness in multimodal large language models, facilitating better reasoning.
Empirical evaluations show dramatic enhancements in tasks like multimodal sarcasm detection, surpassing state-of-the-art methods.
Using counterfactual examples, the model distinguishes between core semantics and spurious contexts effectively.
Engaging dynamic routing within the Mixture-of-Experts architecture allows selective activation of debiasing experts.

Wu et al. (2025) studied this question.

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