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cs.CL2024
Optimal Query Allocation in Extractive QA with LLMs: A Learning-to-Defer Framework with Theoretical Guarantees
Yannis Montreuil, Shu Heng Yeo, Axel Carlier +2
Large Language Models excel in generative tasks but exhibit inefficiencies in structured text selection, particularly in extractive question answering. This challenge is magnified…
stat.ML2024
A Two-Stage Learning-to-Defer Approach for Multi-Task Learning
Yannis Montreuil, Shu Heng Yeo, Axel Carlier +2
The Two-Stage Learning-to-Defer (L2D) framework has been extensively studied for classification and, more recently, regression tasks. However, many real-world applications require…