Search Results for author:
Found 12 papers, 8 papers with code
PRODIGy: a PROfile-based DIalogue Generation dataset
Providing dialogue agents with a profile representation can improve their consistency and coherence, leading to better conversations.
Benchmarking the Generation of Fact Checking Explanations
Results show that in justification production summarization benefits from the claim information, and, in particular, that a claim-driven extractive step improves abstractive summarization performances.
Human-Machine Collaboration Approaches to Build a Dialogue Dataset for Hate Speech Countering
Fighting online hate speech is a challenge that is usually addressed using Natural Language Processing via automatic detection and removal of hate content.
Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Study
In this work, we present an extensive study on the use of pre-trained language models for the task of automatic Counter Narrative (CN) generation to fight online hate speech in English.
Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speech
Undermining the impact of hateful content with informed and non-aggressive responses, called counter narratives, has emerged as a possible solution for having healthier online communities.
Empowering NGOs in Countering Online Hate Messages
In this paper, we introduce a novel ICT platform that NGO operators can use to monitor and analyze social media data, along with a counter-narrative suggestion tool.
Towards Knowledge-Grounded Counter Narrative Generation for Hate Speech
Tackling online hatred using informed textual responses - called counter narratives - has been brought under the spotlight recently.
Toward Stance-based Personas for Opinionated Dialogues
In the context of chit-chat dialogues it has been shown that endowing systems with a persona profile is important to produce more coherent and meaningful conversations.
Generating Counter Narratives against Online Hate Speech: Data and Strategies
Recently research has started focusing on avoiding undesired effects that come with content moderation, such as censorship and overblocking, when dealing with hatred online.
Generating Challenge Datasets for Task-Oriented Conversational Agents through Self-Play
End-to-end neural approaches are becoming increasingly common in conversational scenarios due to their promising performances when provided with sufficient amount of data.
CONAN - COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech
Although there is an unprecedented effort to provide adequate responses in terms of laws and policies to hate content on social media platforms, dealing with hatred online is still a tough problem.
FASTDial: Abstracting Dialogue Policies for Fast Development of Task Oriented Agents
We present a novel abstraction framework called FASTDial for designing task oriented dialogue agents, built on top of the OpenDial toolkit.
