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Improving Uncertainty Quantification in Large Language Models via
  Semantic Embeddings

Improving Uncertainty Quantification in Large Language Models via Semantic Embeddings

30 October 2024
Yashvir S. Grewal
Edwin V. Bonilla
Thang D. Bui
    UQCV
ArXivPDFHTML

Papers citing "Improving Uncertainty Quantification in Large Language Models via Semantic Embeddings"

3 / 3 papers shown
Title
Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review
Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review
Toghrul Abbasli
Kentaroh Toyoda
Yuan Wang
Leon Witt
Muhammad Asif Ali
Yukai Miao
Dan Li
Qingsong Wei
UQCV
92
0
0
25 Apr 2025
Semantic Volume: Quantifying and Detecting both External and Internal Uncertainty in LLMs
Semantic Volume: Quantifying and Detecting both External and Internal Uncertainty in LLMs
Xiaomin Li
Zhou Yu
Ziji Zhang
Yingying Zhuang
Siyang Song
Narayanan Sadagopan
Anurag Beniwal
HILM
60
0
0
28 Feb 2025
Uncertainty-Aware Step-wise Verification with Generative Reward Models
Uncertainty-Aware Step-wise Verification with Generative Reward Models
Zihuiwen Ye
Luckeciano C. Melo
Younesse Kaddar
Phil Blunsom
Shivalika Singh
Yarin Gal
LRM
49
0
0
16 Feb 2025
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