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02/07/2023
Towards a Deeper Understanding of Concept Bottleneck Models Through End-to-End Explanation
Concept Bottleneck Models (CBMs) first map raw input(s) to a vector of h...
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02/01/2022
Politics and Virality in the Time of Twitter: A Large-Scale Cross-Party Sentiment Analysis in Greece, Spain and United Kingdom
Social media has become extremely influential when it comes to policy ma...
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12/10/2021
AAAI FSS-21: Artificial Intelligence in Government and Public Sector Proceedings
Proceedings of the AAAI Fall Symposium on Artificial Intelligence in Gov...
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11/17/2021
Guiding Generative Language Models for Data Augmentation in Few-Shot Text Classification
Data augmentation techniques are widely used for enhancing the performan...
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10/15/2021
Using DeepProbLog to perform Complex Event Processing on an Audio Stream
In this paper, we present an approach to Complex Event Processing (CEP) ...
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08/06/2021
Deriving Disinformation Insights from Geolocalized Twitter Callouts
This paper demonstrates a two-stage method for deriving insights from so...
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05/13/2021
Providing Assurance and Scrutability on Shared Data and Machine Learning Models with Verifiable Credentials
Adopting shared data resources requires scientists to place trust in the...
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04/05/2021
Tokenising behaviour change: optimising blockchain technology for sustainable transport interventions
Transport makes an impact across SDGs, encompassing climate change, heal...
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03/05/2021
A framework for fostering transparency in shared artificial intelligence models by increasing visibility of contributions
Increased adoption of artificial intelligence (AI) systems into scientif...
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11/09/2020
AAAI FSS-20: Artificial Intelligence in Government and Public Sector Proceedings
Proceedings of the AAAI Fall Symposium on Artificial Intelligence in Gov...
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10/27/2020
Predicting Themes within Complex Unstructured Texts: A Case Study on Safeguarding Reports
The task of text and sentence classification is associated with the need...
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10/27/2020
An Experimentation Platform for Explainable Coalition Situational Understanding
We present an experimentation platform for coalition situational underst...
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09/09/2020
Towards a Modelling Framework for Self-Sovereign Identity Systems
Self-sovereign Identity promises to give users control of their own data...
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09/07/2020
A Hybrid Neuro-Symbolic Approach for Complex Event Processing
Training a model to detect patterns of interrelated events that form sit...
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04/06/2020
Certifying Provenance of Scientific Datasets with Self-sovereign Identity and Verifiable Credentials
In order to increase the value of scientific datasets and improve resear...
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03/31/2020
Explaining Motion Relevance for Activity Recognition in Video Deep Learning Models
A small subset of explainability techniques developed initially for imag...
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03/30/2020
The current state of automated argumentation theory: a literature review
Automated negotiation can be an efficient method for resolving conflict ...
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03/30/2020
Increasing negotiation performance at the edge of the network
Automated negotiation has been used in a variety of distributed settings...
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11/29/2019
Sanity Checks for Saliency Metrics
Saliency maps are a popular approach to creating post-hoc explanations o...
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11/04/2019
AAAI FSS-19: Artificial Intelligence in Government and Public Sector Proceedings
Proceedings of the AAAI Fall Symposium on Artificial Intelligence in Gov...
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10/16/2019
Explainable AI for Intelligence Augmentation in Multi-Domain Operations
Central to the concept of multi-domain operations (MDO) is the utilizati...
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09/16/2019
BMVC 2019: Workshop on Interpretable and Explainable Machine Vision
Proceedings of the BMVC 2019 Workshop on Interpretable and Explainable M...
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09/07/2019
Explainable Deep Learning for Video Recognition Tasks: A Framework Recommendations
The popularity of Deep Learning for real-world applications is ever-grow...
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08/05/2019
Discriminating Spatial and Temporal Relevance in Deep Taylor Decompositions for Explainable Activity Recognition
Current techniques for explainable AI have been applied with some succes...
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07/08/2019
Quantifying Transparency of Machine Learning Systems through Analysis of Contributions
Increased adoption and deployment of machine learning (ML) models into b...
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06/05/2019
Deep Q-Learning for Directed Acyclic Graph Generation
We present a method to generate directed acyclic graphs (DAGs) using dee...
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04/08/2019
Towards Traceability in Data Ecosystems using a Bill of Materials Model
Researchers and scientists use aggregations of data from a diverse combi...
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04/05/2019
A Conceptual Architecture for Contractual Data Sharing in a Decentralised Environment
Machine Learning systems rely on data for training, input and ongoing fe...
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10/14/2018
AAAI FSS-18: Artificial Intelligence in Government and Public Sector Proceedings
Proceedings of the AAAI Fall Symposium on Artificial Intelligence in Gov...
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09/29/2018
Stakeholders in Explainable AI
There is general consensus that it is important for artificial intellige...
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09/28/2018
Hows and Whys of Artificial Intelligence for Public Sector Decisions: Explanation and Evaluation
Evaluation has always been a key challenge in the development of artific...
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09/25/2018
Defining the Collective Intelligence Supply Chain
Organisations are increasingly open to scrutiny, and need to be able to ...
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09/20/2018
Uncertainty Aware AI ML: Why and How
This paper argues the need for research to realize uncertainty-aware art...
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06/20/2018
Interpretable to Whom? A Role-based Model for Analyzing Interpretable Machine Learning Systems
Several researchers have argued that a machine learning system's interpr...
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07/11/2011
Rule-Based Semantic Sensing
Rule-Based Systems have been in use for decades to solve a variety of pr...
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07/08/2011