NLPExplorer

NL4XAI - 2020

Total Papers:- 15

Total Papers accross all years:- 15

Total Citations :- 0

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Explaining Bayesian Networks in Natural Language: State of the Art and Challenges

Conor Hennessy | Alberto Bugarín | Ehud Reiter |

Generating Explanations of Action Failures in a Cognitive Robotic Architecture

Ravenna Thielstrom | Antonio Roque | Meia Chita-Tegmark | Matthias Scheutz |

Content Selection for Explanation Requests in Customer-Care Domain

Toward Natural Language Mitigation Strategies for Cognitive Biases in Recommender Systems

Alisa Rieger | Mariët Theune | Nava Tintarev |

Towards Generating Effective Explanations of Logical Formulas: Challenges and Strategies

Alexandra Mayn | Kees van Deemter |

The Natural Language Pipeline, Neural Text Generation and Explainability

Juliette Faille | Albert Gatt | Claire Gardent |

Argumentation Theoretical Frameworks for Explainable Artificial Intelligence

Martijn Demollin | Qurat-Ul-Ain Shaheen | Katarzyna Budzynska | Carles Sierra |

When to explain: Identifying explanation triggers in human-agent interaction

Lea Krause | Piek Vossen |

Explaining data using causal Bayesian networks

Jaime Sevilla |

Bias in AI-systems: A multi-step approach

Eirini Ntoutsi |

Learning from Explanations and Demonstrations: A Pilot Study

Towards Harnessing Natural Language Generation to Explain Black-box Models

Ettore Mariotti | Jose M. Alonso | Albert Gatt |

ExTRA: Explainable Therapy-Related Annotations

Automatically explaining health information

Emiel Khramer |