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cs.CL2025
The Consistency Hypothesis in Uncertainty Quantification for Large Language Models
Quan Xiao, Debarun Bhattacharjya, Balaji Ganesan +5
Estimating the confidence of large language model (LLM) outputs is essential for real-world applications requiring high user trust. Black-box uncertainty quantification (UQ) method…
cs.CL2025
Rationalization Models for Text-to-SQL
Gaetano Rossiello, Nhan Pham, Michael Glass +2
We introduce a framework for generating Chain-of-Thought (CoT) rationales to enhance text-to-SQL model fine-tuning. These rationales consist of intermediate SQL statements and expl…