Expert Stance Graphs for Computational Argumentation
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Argument MiningSimilar Papers 제목 키워드 기반
Structure-Aware Encodings of Argumentation Properties for Clique-width
Structural measures of graphs, such as treewidth, are central tools in computational complexity resulting in efficient algorithms when exploiting the parameter. It is even known that modern SAT solvers work efficiently o…
Syntopical Graphs for Computational Argumentation Tasks
Approaches to computational argumentation tasks such as stance detection and aspect detection have largely focused on the text of independent claims, losing out on potentially valuable context provided by the rest of the…
Stance DetectionLeveraging Large Language Models for Causal Discovery: a Constraint-based, Argumentation-driven Approach
Causal discovery seeks to uncover causal relations from data, typically represented as causal graphs, and is essential for predicting the effects of interventions. While expert knowledge is required to construct principl…
Interpreting Neural Networks as Gradual Argumentation Frameworks (Including Proof Appendix)
We show that an interesting class of feed-forward neural networks can be understood as quantitative argumentation frameworks. This connection creates a bridge between research in Formal Argumentation and Machine Learning…
BIG-bench Machine LearningARGORA: Orchestrated Argumentation for Causally Grounded LLM Reasoning and Decision Making
Existing multi-expert LLM systems gather diverse perspectives but combine them through simple aggregation, obscuring which arguments drove the final decision. We introduce ARGORA, a framework that organizes multi-expert …
Decision Making