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

Jayanth Srinivasa

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

11 / 11 papers shown

Title
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 94 0 0 25 Apr 2025
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
Representation Engineering for Large-Language Models: Survey and Research Challenges Lukasz Bartoszcze Sarthak Munshi Bryan Sukidi Jennifer Yen Zejia Yang David Williams-King Linh Le Kosi Asuzu Carsten Maple 102 0 0 24 Feb 2025
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 29 0 03 Oct 2024
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 Samuel Marks Max Tegmark HILM 102 173 0 10 Oct 2023
The Internal State of an LLM Knows When It's Lying A. Azaria Tom Michael Mitchell HILM 218 301 0 26 Apr 2023
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 96 0 30 Sep 2022
Unsolved Problems in ML Safety Dan Hendrycks Nicholas Carlini John Schulman Jacob Steinhardt 186 275 0 28 Sep 2021
The Intrinsic Dimension of Images and Its Impact on Learning Phillip E. Pope Chen Zhu Ahmed Abdelkader Micah Goldblum Tom Goldstein 197 261 0 18 Apr 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,145 0 06 Jun 2015