On guaranteed optimal robust explanations for NLP models
We build on abduction-based explanations for machine learning and develop a method for computing local explanations for neural network models in natural language processing (NLP). Our explanations comprise a subset of the words of the input text that satisfies two key features: optimality w.r.t. a u...
Κύριοι συγγραφείς: | La Malfa, E, Michelmore, R, Zbrzezny, AM, Paoletti, N, Kwiatkowska, M |
---|---|
Μορφή: | Conference item |
Γλώσσα: | English |
Έκδοση: |
International Joint Conferences on Artificial Intelligence
2021
|
Παρόμοια τεκμήρια
Παρόμοια τεκμήρια
-
Statistical guarantees for the robustness of Bayesian neural networks
ανά: Cardelli, L, κ.ά.
Έκδοση: (2019) -
Towards Faithful Model Explanation in NLP: A Survey
ανά: Qing Lyu, κ.ά.
Έκδοση: (2024-07-01) -
Explanation-Based Human Debugging of NLP Models: A Survey
ανά: Piyawat Lertvittayakumjorn, κ.ά.
Έκδοση: (2021-01-01) -
Robustness guarantees for deep neural networks on videos
ανά: Kwiatkowska, M, κ.ά.
Έκδοση: (2020) -
Safety and robustness for deep learning with provable guarantees (keynote)
ανά: Kwiatkowska, M
Έκδοση: (2019)