Papers by Antonio Rago
Can Large Language Models perform Relation-based Argument Mining? (2025.coling-main)
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| Challenge: | Existing methods for RbAM fail to perform satisfactorily across different datasets. |
| Approach: | They propose to use relation-based argument mining to determine agreement (support) and disagreement (attack) relations amongst textual arguments in binary and ternary settings. |
| Outcome: | The proposed method outperforms the best performing (RoBERTa-based) baseline on two open-source LLMs and with GPT-3.5-turbo on several datasets for (binary and ternary) RbAM. |
Evaluating Uncertainty Quantification Methods in Argumentative Large Language Models (2025.findings-emnlp)
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| Challenge: | ArgLLMs are an explainable LLM framework for decision-making based on computational argumentation in which uncertainty quantification plays a critical role. |
| Approach: | They propose to integrate LLM UQ methods into argumentative LLMs to evaluate their performance on claim verification tasks. |
| Outcome: | The proposed method outperforms more complex approaches on claim verification tasks. |