A Human-Grounded Evaluation Benchmark for Local Explanations of Machine Learning

16 January 2018

Papers citing "A Human-Grounded Evaluation Benchmark for Local Explanations of Machine Learning"

25 / 25 papers shown

Title
Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction Melkamu Mersha Khang Lam Joseph Wood Ali AlShami Jugal Kalita XAI AI4TS 99 28 0 30 Aug 2024
Predictability and Comprehensibility in Post-Hoc XAI Methods: A User-Centered Analysis Anahid N. Jalali Bernhard Haslhofer Simone Kriglstein Andreas Rauber FAtt 57 4 0 21 Sep 2023
Explainable Goal Recognition: A Framework Based on Weight of Evidence Abeer Alshehri Tim Miller Mor Vered 50 3 0 09 Mar 2023
Towards Human-Centred Explainability Benchmarks For Text Classification Viktor Schlegel Erick Mendez Guzman Riza Batista-Navarro 51 5 0 10 Nov 2022
Explainable AI for clinical and remote health applications: a survey on tabular and time series data Flavio Di Martino Franca Delmastro AI4TS 33 91 0 14 Sep 2022
An Interpretability Evaluation Benchmark for Pre-trained Language Models Ya-Ming Shen Lijie Wang Ying-Cong Chen Xinyan Xiao Jing Liu Hua Wu 47 4 0 28 Jul 2022
Interpretation Quality Score for Measuring the Quality of interpretability methods Sean Xie Soroush Vosoughi Saeed Hassanpour XAI 48 5 0 24 May 2022
A Fine-grained Interpretability Evaluation Benchmark for Neural NLP Lijie Wang Yaozong Shen Shu-ping Peng Shuai Zhang Xinyan Xiao Hao Liu Hongxuan Tang Ying-Cong Chen Hua Wu Haifeng Wang ELM 44 21 0 23 May 2022
Towards Explainable Evaluation Metrics for Natural Language Generation Christoph Leiter Piyawat Lertvittayakumjorn M. Fomicheva Wei Zhao Yang Gao Steffen Eger AAML ELM 43 20 0 21 Mar 2022
Framework for Evaluating Faithfulness of Local Explanations S. Dasgupta Nave Frost Michal Moshkovitz FAtt 149 61 0 01 Feb 2022
On Two XAI Cultures: A Case Study of Non-technical Explanations in Deployed AI System Helen Jiang Erwen Senge 34 7 0 02 Dec 2021
Trustworthy AI: From Principles to Practices Yue Liu Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 127 358 0 04 Oct 2021
Pitfalls of Explainable ML: An Industry Perspective Sahil Verma Aditya Lahiri John P. Dickerson Su-In Lee XAI 21 9 0 14 Jun 2021
Improving Attribution Methods by Learning Submodular Functions Piyushi Manupriya Tarun Ram Menta S. Jagarlapudi V. Balasubramanian TDI 35 6 0 19 Apr 2021
VitrAI -- Applying Explainable AI in the Real World Marc Hanussek Falko Kötter Maximilien Kintz Jens Drawehn 17 2 0 12 Feb 2021
Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs Harini Suresh Steven R. Gomez K. Nam Arvind Satyanarayan 39 128 0 24 Jan 2021
Dissonance Between Human and Machine Understanding Zijian Zhang Jaspreet Singh U. Gadiraju Avishek Anand 59 74 0 18 Jan 2021
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 36 398 0 19 Oct 2020
What Do You See? Evaluation of Explainable Artificial Intelligence (XAI) Interpretability through Neural Backdoors Yi-Shan Lin Wen-Chuan Lee Z. Berkay Celik XAI 46 94 0 22 Sep 2020
A simple defense against adversarial attacks on heatmap explanations Laura Rieger Lars Kai Hansen FAtt AAML 38 37 0 13 Jul 2020
Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey Arun Das P. Rad XAI 49 593 0 16 Jun 2020
Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness? Alon Jacovi Yoav Goldberg XAI 53 574 0 07 Apr 2020
Predicting Model Failure using Saliency Maps in Autonomous Driving Systems Sina Mohseni Akshay V. Jagadeesh Zhangyang Wang 32 13 0 19 May 2019
Explainability in Human-Agent Systems A. Rosenfeld A. Richardson XAI 32 203 0 17 Apr 2019
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems Sina Mohseni Niloofar Zarei Eric D. Ragan 41 102 0 28 Nov 2018