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Found 5 papers, 3 papers with code
Learning Decomposable and Debiased Representations via Attribute-Centric Information Bottlenecks
Biased attributes, spuriously correlated with target labels in a dataset, can problematically lead to neural networks that learn improper shortcuts for classifications and limit their capabilities for out-of-distribution (OOD) generalization.
Interpreting Answers to Yes-No Questions in User-Generated Content
Interpreting answers to yes-no questions in social media is difficult.
Interpreting Indirect Answers to Yes-No Questions in Multiple Languages
Experimental results demonstrate that monolingual fine-tuning is beneficial if training data can be obtained via distant supervision for the language of interest (5 languages).
Concept-Centric Transformers: Enhancing Model Interpretability through Object-Centric Concept Learning within a Shared Global Workspace
Many interpretable AI approaches have been proposed to provide plausible explanations for a model's decision-making.
Adversarial Demonstration Attacks on Large Language Models
We propose a novel attack method named advICL, which aims to manipulate only the demonstration without changing the input to mislead the models.
