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cs.CL2024
SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models
Xiang Gao, Jiaxin Zhang, Lalla Mouatadid +1
In recent years, large language models (LLMs) have become increasingly prevalent, offering remarkable text generation capabilities. However, a pressing challenge is their tendency…
cs.CL2024
Customizing Language Model Responses with Contrastive In-Context Learning
Xiang Gao, Kamalika Das
Large language models (LLMs) are becoming increasingly important for machine learning applications. However, it can be challenging to align LLMs with our intent, particularly when…