SHAP-based explanation methods: a review for NLP interpretability
E Mosca, F Szigeti, S Tragianni… - Proceedings of the …, 2022 - aclanthology.org
Abstract Model explanations are crucial for the transparent, safe, and trustworthy
deployment of machine learning models. The SHapley Additive exPlanations (SHAP) …
deployment of machine learning models. The SHapley Additive exPlanations (SHAP) …
A Benchmark Dataset to Distinguish Human-Written and Machine-Generated Scientific Papers
As generative NLP can now produce content nearly indistinguishable from human writing, it
is becoming difficult to identify genuine research contributions in academic writing and …
is becoming difficult to identify genuine research contributions in academic writing and …
Uncovering trauma in genocide tribunals: An NLP approach using the Genocide Transcript Corpus
This paper applies Natural Language Processing (NLP) methods to analyze the exposure to
trauma experienced by witnesses in international criminal tribunals when testifying in court …
trauma experienced by witnesses in international criminal tribunals when testifying in court …
Explainable AI for the Human-Centric Development of NLP Models: Working Towards more Interpretable, Robust, and Controllable Models
E Mosca - 2024 - mediatum.ub.tum.de
Larger and more complex models have consistently raised the performance bar in most
Natural Language Processing (NLP) applications, exhibiting a growing presence in society …
Natural Language Processing (NLP) applications, exhibiting a growing presence in society …
Methods for the classification of data from open-ended questions in surveys
C Landesvatter - 2024 - madoc.bib.uni-mannheim.de
This dissertation investigates techniques for analyzing open-ended survey responses, which
are typically short and lack contextual information. Specialized methods, such as word …
are typically short and lack contextual information. Specialized methods, such as word …