Papers by Jordan Massiah
Bayesian Prompt Ensembles: Model Uncertainty Estimation for Black-Box Large Language Models (2024.findings-acl)
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| Challenge: | Existing approaches to quantify uncertainty of pre-trained large language models require specific architectures or retraining strategies. |
| Approach: | They propose a Bayesian Prompts Ensemble approach to accurately quantify LLM uncertainty . they compute output probabilities through a weighted ensemble of different task instruction prompts . |
| Outcome: | The proposed approach achieves significantly superior calibration over baselines over a range of natural language classification tasks. |