Papers with decision-making based

2 papers
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.
Can Large Language Models Effectively Support Decision-Making in Sudden Emergencies? (2026.findings-acl)

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Challenge: Existing research has focused on the earlier stages of emergency response . lack of suitable datasets for reliable and compliance-aware decision-oriented modeling and evaluation is limiting current research .
Approach: They propose a first real-world emergency decision-making dataset EDM-Bench . they propose 'rule-enhanced reasoning framework' that integrates external regulatory knowledge with constrained inference mechanisms to improve both decision safety and interpretability.
Outcome: The proposed framework improves decision safety and interpretability by integrating regulatory knowledge with constrained inference mechanisms.

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