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cs.CL2024
Understanding the Impact of Confidence in Retrieval Augmented Generation: A Case Study in the Medical Domain
Shintaro Ozaki, Yuta Kato, Siyuan Feng +8
Retrieval Augmented Generation (RAG) complements the knowledge of Large Language Models (LLMs) by leveraging external information to enhance response accuracy for queries. This app…
cs.CL2024
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks
Wataru Hashimoto, Hidetaka Kamigaito, Taro Watanabe
Trustworthiness in model predictions is crucial for safety-critical applications in the real world. However, deep neural networks often suffer from the issues of uncertainty estima…
cs.CL2024
Are Data Augmentation Methods in Named Entity Recognition Applicable for Uncertainty Estimation?
Wataru Hashimoto, Hidetaka Kamigaito, Taro Watanabe
This work investigates the impact of data augmentation on confidence calibration and uncertainty estimation in Named Entity Recognition (NER) tasks. For the future advance of NER i…