Papers with model bias learning

1 papers
MMSD2.0: Towards a Reliable Multi-modal Sarcasm Detection System (2023.findings-acl)

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Challenge: Existing benchmarks for multi-modal sarcasm detection have some shortcomings . a new framework can leverage multi-grained cues from multiple perspectives for multimodal detection .
Approach: They propose a correction dataset that removes spurious cues and re-annotates the unreasonable samples.
Outcome: The proposed framework outperforms the existing benchmarks in multi-modal sarcasm detection.

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