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This open access book constitutes the proceedings of the First International Conference on Robust Argumentation Machines, RATIO 2024, which took place in Bielefeld, Germany, during June 5-7, 2024.
The 20 full papers and 1 short paper included in the proceedings were carefully reviewed and selected from 24 submissions. They were organized in topical sections as follows:
Argument Mining; Debate Analysis and Deliberation; Argument Acquisition, Annotation and Quality Assessment; Computational Models of Argumentation; Interactive Argumentation, Recommendation and Personalization; and Argument Search and Retrieval.
Argument Mining.- Natural language hypotheses in scientific papers and how to tame them: Suggested steps for formalizing complex scientific claims.- Weakly Supervised Claim Localization in Scientific Abstracts.- Argument Mining of Attack and Support Patterns in Dialogical Conversations with Sequential Pattern Mining.- Cluster-Specific Rule Mining for Argumentation-Based Classification.- Debate Analysis and Deliberation.- Automatic Analysis of Political Debates and Manifestos: Successes and Challenges.- PAKT: Perspectivized Argumentation Knowledge Graph and Tool for Deliberation Analysis.- PolArg: Unsupervised Polarity Prediction of Arguments in Real-Time Online Conversations.- Argument Acquisition, Annotation and Quality.- Assessment Are Large Language Models Reliable Argument Quality Annotators.- The Impact of Argument Arrangement on Essay Scoring.- Finding Argument Fragments on Social Media with Corpus Queries and LLMs.- Computational Models of Argumentation.- Enhancing Abstract Argumentation Solvers with Machine Learning-Guided Heuristics: A Feasibility Study.- Ranking Transition-based Medical Recommendations using Assumption-based Argumentation.- Argumentation-based Probabilistic Causal Reasoning.- From Networks to Narratives: Bayes Nets and the problems of argumentation.- Enhancing Argument Generation using Bayesian Networks.- “Do not disturb my circles!” Identifying the Type of Counterfactual at Hand.- Interactive Argumentation, Recommendation and Personalization.- BEA: Building Engaging Argumentation.- Deciphering Personal Argument Styles – A Comprehensive Approach to Analyzing Linguistic Properties of Argument Preferences.- Argument Search and Retrieval.- Extending the Comparative Argumentative Machine: Multilingualism and Stance Detection.- Objective Argument Summarization in Search.- ArgServices: A Microservice-Based Architecture for Argumentation Machines.
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