A Training-Free Debiasing Framework with Counterfactual Reasoning for Conversational Emotion Detection
Geng Tu,
Ran Jing,
Bin Liang
et al.
Abstract:Unintended dataset biases typically exist in existing Emotion Recognition in Conversations (ERC) datasets, including label bias, where models favor the majority class due to imbalanced training data, as well as the speaker and neutral word bias, where models make unfair predictions because of excessive correlations between specific neutral words or speakers and classes. However, previous studies in ERC generally focus on capturing context-sensitive and speaker-sensitive dependencies, ignoring the unintended da… Show more
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