A Review on Explainability in Multimodal Deep Neural Nets

17 May 2021

Papers citing "A Review on Explainability in Multimodal Deep Neural Nets"

48 / 48 papers shown

Title
Multi-modal biometric authentication: Leveraging shared layer architectures for enhanced security Vatchala S Yogesh C Yeshwanth Govindarajan Krithik Raja M Vishal Pramav Amirtha Ganesan Aashish Vinod A Dharun Ramesh 32 1 0 04 Nov 2024
Why context matters in VQA and Reasoning: Semantic interventions for VLM input modalities Kenza Amara Lukas Klein Carsten T. Lüth Paul Jäger Hendrik Strobelt Mennatallah El-Assady 25 1 0 02 Oct 2024
Do We Trust What They Say or What They Do? A Multimodal User Embedding Provides Personalized Explanations Zhicheng Ren Zhiping Xiao Yizhou Sun 38 0 0 04 Sep 2024
MicroXercise: A Micro-Level Comparative and Explainable System for Remote Physical Therapy Hanchen David Wang Nibraas Khan Anna Chen Nilanjan Sarkar Pamela Wisniewski Meiyi Ma 37 0 0 06 Aug 2024
A Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications V. Guarrasi Fatih Aksu Camillo Maria Caruso Francesco Di Feola Aurora Rofena Filippo Ruffini Paolo Soda OffRL MedIm AI4CE 20 12 0 02 Aug 2024
Fairness and Bias in Multimodal AI: A Survey Tosin P. Adewumi Lama Alkhaled Namrata Gurung G. V. Boven Irene Pagliai 58 9 0 27 Jun 2024
A Survey on Safe Multi-Modal Learning System Tianyi Zhao Liangliang Zhang Yao Ma Lu Cheng 52 9 0 08 Feb 2024
Review of multimodal machine learning approaches in healthcare "Felix H. Krones Umar Marikkar Guy Parsons Adam Szmul Adam Mahdi 37 27 0 04 Feb 2024
CrisisKAN: Knowledge-infused and Explainable Multimodal Attention Network for Crisis Event Classification Shubham Gupta Nandini Saini Suman Kundu Debasis Das 18 6 0 11 Jan 2024
Large Language Models in Law: A Survey Jinqi Lai Wensheng Gan Jiayang Wu Zhenlian Qi Philip S. Yu ELM AILaw 28 70 0 26 Nov 2023
NERIF: GPT-4V for Automatic Scoring of Drawn Models Gyeong-Geon Lee Xiaoming Zhai 13 9 0 21 Nov 2023
Enhancing the machine vision performance with multi-spectral light sources Feng Zhang Rui Bao Congqi Dai Wanlu Zhang Shu Liu R. Guo 15 0 0 20 Oct 2023
MultiModN- Multimodal, Multi-Task, Interpretable Modular Networks Vinitra Swamy Malika Satayeva Jibril Frej Thierry Bossy Thijs Vogels Martin Jaggi Tanja Kaser Mary-Anne Hartley 18 11 0 25 Sep 2023
Towards Vision-Language Mechanistic Interpretability: A Causal Tracing Tool for BLIP Vedant Palit Rohan Pandey Aryaman Arora Paul Pu Liang 31 20 0 27 Aug 2023
Causal Intersectionality and Dual Form of Gradient Descent for Multimodal Analysis: a Case Study on Hateful Memes Yosuke Miyanishi M. Nguyen 28 2 0 19 Aug 2023
Explainable Multi-View Deep Networks Methodology for Experimental Physics Nadav Schneider Muriel Tzdaka G. Sturm Guy Lazovski G. Bar G. Oren R. Gvishi Gal Oren 23 0 0 16 Aug 2023
Impact of Feature Encoding on Malware Classification Explainability E. Manai M. Mejri Jaouhar Fattahi 24 1 0 10 Jul 2023
Requirements for Explainability and Acceptance of Artificial Intelligence in Collaborative Work Sabine Theis Sophie F. Jentzsch Fotini Deligiannaki C. Berro A. Raulf C. Bruder 23 8 0 27 Jun 2023
Employing Multimodal Machine Learning for Stress Detection Rahee Walambe Pranav Nayak Ashmit Bhardwaj K. Kotecha 11 48 0 15 Jun 2023
Multimodal Explainable Artificial Intelligence: A Comprehensive Review of Methodological Advances and Future Research Directions N. Rodis Christos Sardianos Panagiotis I. Radoglou-Grammatikis Panagiotis G. Sarigiannidis Iraklis Varlamis Georgios Th. Papadopoulos 25 22 0 09 Jun 2023
IMAD: IMage-Augmented multi-modal Dialogue Viktor Moskvoretskii Anton Frolov Denis Kuznetsov 22 4 0 17 May 2023
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources Suraj Rajendran Weishen Pan M. Sabuncu Yong Chen Jiayu Zhou Fei Wang 54 14 0 10 May 2023
Interpretable multimodal sentiment analysis based on textual modality descriptions by using large-scale language models Sixia Li S. Okada 32 3 0 07 May 2023
Diagnosing and Rectifying Vision Models using Language Yuhui Zhang Jeff Z. HaoChen Shih-Cheng Huang Kuan-Chieh Jackson Wang James Y. Zou Serena Yeung 20 43 0 08 Feb 2023
Multimodal Explainability via Latent Shift applied to COVID-19 stratification V. Guarrasi L. Tronchin Domenico Albano E. Faiella Deborah Fazzini D. Santucci Paolo Soda 13 22 0 28 Dec 2022
On the Robustness of Explanations of Deep Neural Network Models: A Survey Amlan Jyoti Karthik Balaji Ganesh Manoj Gayala Nandita Lakshmi Tunuguntla Sandesh Kamath V. Balasubramanian XAI FAtt AAML 32 4 0 09 Nov 2022
Towards Human-centered Explainable AI: A Survey of User Studies for Model Explanations Yao Rong Tobias Leemann Thai-trang Nguyen Lisa Fiedler Peizhu Qian Vaibhav Unhelkar Tina Seidel Gjergji Kasneci Enkelejda Kasneci ELM 36 92 0 20 Oct 2022
MMRNet: Improving Reliability for Multimodal Object Detection and Segmentation for Bin Picking via Multimodal Redundancy Yuhao Chen Hayden Gunraj E. Z. Zeng Robbie Meyer Maximilian Gilles Alexander Wong 37 1 0 19 Oct 2022
Fidelity of Ensemble Aggregation for Saliency Map Explanations using Bayesian Optimization Techniques Yannik Mahlau Christian Nolde FAtt 35 0 0 04 Jul 2022
Is Multi-Modal Necessarily Better? Robustness Evaluation of Multi-modal Fake News Detection Jinyin Chen Chengyu Jia Haibin Zheng Ruoxi Chen Chenbo Fu AAML 22 10 0 17 Jun 2022
Improving Multimodal Speech Recognition by Data Augmentation and Speech Representations Dan Oneaţă H. Cucu 19 19 0 27 Apr 2022
Multi-objective optimization determines when, which and how to fuse deep networks: an application to predict COVID-19 outcomes V. Guarrasi Paolo Soda 12 23 0 07 Apr 2022
Explainable Misinformation Detection Across Multiple Social Media Platforms Gargi Joshi Ananya Srivastava Bhargav D. Yagnik Md Musleh Uddin Hasan Zainuddin Saiyed Lubna A Gabralla Ajith Abraham Rahee Walambe K. Kotecha 23 17 0 20 Mar 2022
Emulating Quantum Dynamics with Neural Networks via Knowledge Distillation Yu Yao C. Cao S. Haas Mahak Agarwal Divya Khanna M. Abram 19 4 0 19 Mar 2022
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI Meike Nauta Jan Trienes Shreyasi Pathak Elisa Nguyen Michelle Peters Yasmin Schmitt Jorg Schlotterer M. V. Keulen C. Seifert ELM XAI 28 395 0 20 Jan 2022
Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities Waddah Saeed C. Omlin XAI 36 414 0 11 Nov 2021
HEROHE Challenge: assessing HER2 status in breast cancer without immunohistochemistry or in situ hybridization Eduardo Conde-Sousa João Vale Ming Feng Kele Xu Yin Wang ... Guilherme Aresta Teresa Araújo Paulo Aguiar C. Eloy A. Polónia 24 28 0 08 Nov 2021
Multimodal Co-learning: Challenges, Applications with Datasets, Recent Advances and Future Directions Anil Rahate Rahee Walambe S. Ramanna K. Kotecha 24 135 0 29 Jul 2021
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 255 4,777 0 24 Feb 2021
Unbox the Black-box for the Medical Explainable AI via Multi-modal and Multi-centre Data Fusion: A Mini-Review, Two Showcases and Beyond Guang Yang Qinghao Ye Jun Xia 92 480 0 03 Feb 2021
Beyond VQA: Generating Multi-word Answer and Rationale to Visual Questions Radhika Dua Sai Srinivas Kancheti V. Balasubramanian LRM 38 22 0 24 Oct 2020
Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional Entropies Itai Gat Idan Schwartz A. Schwing Tamir Hazan 55 89 0 21 Oct 2020
Multimodal Research in Vision and Language: A Review of Current and Emerging Trends Shagun Uppal Sarthak Bhagat Devamanyu Hazarika Navonil Majumdar Soujanya Poria Roger Zimmermann Amir Zadeh 23 6 0 19 Oct 2020
Semantics of the Black-Box: Can knowledge graphs help make deep learning systems more interpretable and explainable? Manas Gaur Keyur Faldu A. Sheth 34 113 0 16 Oct 2020
Deep-HOSeq: Deep Higher Order Sequence Fusion for Multimodal Sentiment Analysis Sunny Verma Jiwei Wang Zhefeng Ge Rujia Shen Fan Jin Yang Wang Fang Chen Wei Liu 21 20 0 16 Oct 2020
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 251 3,683 0 28 Feb 2017
Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding Akira Fukui Dong Huk Park Daylen Yang Anna Rohrbach Trevor Darrell Marcus Rohrbach 152 1,465 0 06 Jun 2016