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Characterizing Truthfulness in Large Language Model Generations with
  Local Intrinsic Dimension

Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic Dimension

28 February 2024
Fan Yin
Jayanth Srinivasa
Kai-Wei Chang
    HILM
ArXivPDFHTML

Papers citing "Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic Dimension"

10 / 10 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
Learning on LLM Output Signatures for gray-box LLM Behavior Analysis
Learning on LLM Output Signatures for gray-box LLM Behavior Analysis
Guy Bar-Shalom
Fabrizio Frasca
Derek Lim
Yoav Gelberg
Yftah Ziser
Ran El-Yaniv
Gal Chechik
Haggai Maron
67
0
0
18 Mar 2025
LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations
LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations
Hadas Orgad
Michael Toker
Zorik Gekhman
Roi Reichart
Idan Szpektor
Hadas Kotek
Yonatan Belinkov
HILM
AIFin
61
25
0
03 Oct 2024
Emergence of a High-Dimensional Abstraction Phase in Language Transformers
Emergence of a High-Dimensional Abstraction Phase in Language Transformers
Emily Cheng
Diego Doimo
Corentin Kervadec
Iuri Macocco
Jade Yu
A. Laio
Marco Baroni
112
11
0
24 May 2024
The Geometry of Truth: Emergent Linear Structure in Large Language Model
  Representations of True/False Datasets
The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets
Samuel Marks
Max Tegmark
HILM
102
169
0
10 Oct 2023
The Internal State of an LLM Knows When It's Lying
The Internal State of an LLM Knows When It's Lying
A. Azaria
Tom Michael Mitchell
HILM
218
299
0
26 Apr 2023
Out-of-Distribution Detection and Selective Generation for Conditional
  Language Models
Out-of-Distribution Detection and Selective Generation for Conditional Language Models
Jie Jessie Ren
Jiaming Luo
Yao-Min Zhao
Kundan Krishna
Mohammad Saleh
Balaji Lakshminarayanan
Peter J. Liu
OODD
72
94
0
30 Sep 2022
Unsolved Problems in ML Safety
Unsolved Problems in ML Safety
Dan Hendrycks
Nicholas Carlini
John Schulman
Jacob Steinhardt
186
273
0
28 Sep 2021
The Intrinsic Dimension of Images and Its Impact on Learning
The Intrinsic Dimension of Images and Its Impact on Learning
Phillip E. Pope
Chen Zhu
Ahmed Abdelkader
Micah Goldblum
Tom Goldstein
197
260
0
18 Apr 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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