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The Curious Case of Hallucinatory (Un)answerability: Finding Truths in
  the Hidden States of Over-Confident Large Language Models

The Curious Case of Hallucinatory (Un)answerability: Finding Truths in the Hidden States of Over-Confident Large Language Models

18 October 2023
Aviv Slobodkin
Omer Goldman
Avi Caciularu
Ido Dagan
Shauli Ravfogel
    HILM
    LRM
ArXivPDFHTML

Papers citing "The Curious Case of Hallucinatory (Un)answerability: Finding Truths in the Hidden States of Over-Confident Large Language Models"

8 / 8 papers shown
Title
MAQA: Evaluating Uncertainty Quantification in LLMs Regarding Data Uncertainty
MAQA: Evaluating Uncertainty Quantification in LLMs Regarding Data Uncertainty
Yongjin Yang
Haneul Yoo
Hwaran Lee
56
1
0
13 Aug 2024
"According to ...": Prompting Language Models Improves Quoting from
  Pre-Training Data
"According to ...": Prompting Language Models Improves Quoting from Pre-Training Data
Orion Weller
Marc Marone
Nathaniel Weir
Dawn J Lawrie
Daniel Khashabi
Benjamin Van Durme
HILM
61
44
0
22 May 2023
Poisoning Language Models During Instruction Tuning
Poisoning Language Models During Instruction Tuning
Alexander Wan
Eric Wallace
Sheng Shen
Dan Klein
SILM
90
124
0
01 May 2023
Dissecting Recall of Factual Associations in Auto-Regressive Language
  Models
Dissecting Recall of Factual Associations in Auto-Regressive Language Models
Mor Geva
Jasmijn Bastings
Katja Filippova
Amir Globerson
KELM
183
260
0
28 Apr 2023
Faithfulness-Aware Decoding Strategies for Abstractive Summarization
Faithfulness-Aware Decoding Strategies for Abstractive Summarization
David Wan
Mengwen Liu
Kathleen McKeown
Markus Dreyer
Mohit Bansal
HILM
111
20
0
06 Mar 2023
Calibration of Pre-trained Transformers
Calibration of Pre-trained Transformers
Shrey Desai
Greg Durrett
UQLM
229
288
0
17 Mar 2020
The Bottom-up Evolution of Representations in the Transformer: A Study
  with Machine Translation and Language Modeling Objectives
The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives
Elena Voita
Rico Sennrich
Ivan Titov
179
181
0
03 Sep 2019
What you can cram into a single vector: Probing sentence embeddings for
  linguistic properties
What you can cram into a single vector: Probing sentence embeddings for linguistic properties
Alexis Conneau
Germán Kruszewski
Guillaume Lample
Loïc Barrault
Marco Baroni
196
876
0
03 May 2018
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