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09/02/2023
Explainability for Large Language Models: A Survey
Large language models (LLMs) have demonstrated impressive capabilities i...
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02/03/2023
Improving Interpretability via Explicit Word Interaction Graph Layer
Recent NLP literature has seen growing interest in improving model inter...
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12/19/2022
KNIFE: Knowledge Distillation with Free-Text Rationales
Free-text rationales (FTRs) follow how humans communicate by explaining ...
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12/10/2022
Identifying the Source of Vulnerability in Explanation Discrepancy: A Case Study in Neural Text Classification
Some recent works observed the instability of post-hoc explanations when...
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05/19/2022
Self-augmented Data Selection for Few-shot Dialogue Generation
The natural language generation (NLG) module in task-oriented dialogue s...
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04/17/2022
Pathologies of Pre-trained Language Models in Few-shot Fine-tuning
Although adapting pre-trained language models with few examples has show...
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03/23/2022
Adversarial Training for Improving Model Robustness? Look at Both Prediction and Interpretation
Neural language models show vulnerability to adversarial examples which ...
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01/11/2022
Explaining Prediction Uncertainty of Pre-trained Language Models by Detecting Uncertain Words in Inputs
Estimating the predictive uncertainty of pre-trained language models is ...
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08/11/2021
Perturbing Inputs for Fragile Interpretations in Deep Natural Language Processing
Interpretability methods like Integrated Gradient and LIME are popular c...
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04/09/2021
Explaining Neural Network Predictions on Sentence Pairs via Learning Word-Group Masks
Explaining neural network models is important for increasing their trust...
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10/01/2020
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers
To build an interpretable neural text classifier, most of the prior work...
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04/04/2020
Generating Hierarchical Explanations on Text Classification via Feature Interaction Detection
Generating explanations for neural networks has become crucial for their...
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09/10/2019
