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Knowing What LLMs DO NOT Know: A Simple Yet Effective Self-Detection
  Method
v1v2 (latest)

Knowing What LLMs DO NOT Know: A Simple Yet Effective Self-Detection Method

27 October 2023
Yukun Zhao
Lingyong Yan
Weiwei Sun
Guoliang Xing
Chong Meng
Shuaiqiang Wang
Zhicong Cheng
Zhaochun Ren
Dawei Yin
ArXiv (abs)PDFHTML

Papers citing "Knowing What LLMs DO NOT Know: A Simple Yet Effective Self-Detection Method"

22 / 22 papers shown
Title
Exploring How LLMs Capture and Represent Domain-Specific Knowledge
Exploring How LLMs Capture and Represent Domain-Specific Knowledge
Mirian Hipolito Garcia
Camille Couturier
Daniel Madrigal Diaz
Ankur Mallick
Anastasios Kyrillidis
Robert Sim
Victor Rühle
Saravan Rajmohan
66
1
0
23 Apr 2025
Large Language Models Could Be Rote Learners
Large Language Models Could Be Rote Learners
Yuyang Xu
Renjun Hu
Haochao Ying
Jian Wu
Xing Shi
Wei Lin
ELM
408
0
0
11 Apr 2025
Fact Recall, Heuristics or Pure Guesswork? Precise Interpretations of Language Models for Fact Completion
Fact Recall, Heuristics or Pure Guesswork? Precise Interpretations of Language Models for Fact Completion
Denitsa Saynova
Lovisa Hagström
Moa Johansson
Richard Johansson
Marco Kuhlmann
HILM
107
1
0
18 Oct 2024
Do Not Design, Learn: A Trainable Scoring Function for Uncertainty Estimation in Generative LLMs
Do Not Design, Learn: A Trainable Scoring Function for Uncertainty Estimation in Generative LLMs
D. Yaldiz
Yavuz Faruk Bakman
Baturalp Buyukates
Chenyang Tao
Anil Ramakrishna
Dimitrios Dimitriadis
Jieyu Zhao
Salman Avestimehr
113
8
0
17 Jun 2024
Can ChatGPT Understand Too? A Comparative Study on ChatGPT and
  Fine-tuned BERT
Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT
Qihuang Zhong
Liang Ding
Juhua Liu
Bo Du
Dacheng Tao
AI4MH
108
245
0
19 Feb 2023
Calibration Meets Explanation: A Simple and Effective Approach for Model
  Confidence Estimates
Calibration Meets Explanation: A Simple and Effective Approach for Model Confidence Estimates
Dongfang Li
Baotian Hu
Qingcai Chen
42
8
0
06 Nov 2022
Language Models (Mostly) Know What They Know
Language Models (Mostly) Know What They Know
Saurav Kadavath
Tom Conerly
Amanda Askell
T. Henighan
Dawn Drain
...
Nicholas Joseph
Benjamin Mann
Sam McCandlish
C. Olah
Jared Kaplan
ELM
122
830
0
11 Jul 2022
PaLM: Scaling Language Modeling with Pathways
PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery
Sharan Narang
Jacob Devlin
Maarten Bosma
Gaurav Mishra
...
Kathy Meier-Hellstern
Douglas Eck
J. Dean
Slav Petrov
Noah Fiedel
PILMLRM
524
6,293
0
05 Apr 2022
Training Verifiers to Solve Math Word Problems
Training Verifiers to Solve Math Word Problems
K. Cobbe
V. Kosaraju
Mohammad Bavarian
Mark Chen
Heewoo Jun
...
Jerry Tworek
Jacob Hilton
Reiichiro Nakano
Christopher Hesse
John Schulman
ReLMOffRLLRM
342
4,569
0
27 Oct 2021
Unsolved Problems in ML Safety
Unsolved Problems in ML Safety
Dan Hendrycks
Nicholas Carlini
John Schulman
Jacob Steinhardt
242
293
0
28 Sep 2021
Knowledgeable or Educated Guess? Revisiting Language Models as Knowledge
  Bases
Knowledgeable or Educated Guess? Revisiting Language Models as Knowledge Bases
Boxi Cao
Hongyu Lin
Xianpei Han
Le Sun
Lingyong Yan
M. Liao
Tong Xue
Jin Xu
46
135
0
17 Jun 2021
Reducing conversational agents' overconfidence through linguistic
  calibration
Reducing conversational agents' overconfidence through linguistic calibration
Sabrina J. Mielke
Arthur Szlam
Emily Dinan
Y-Lan Boureau
276
169
0
30 Dec 2020
Recipes for building an open-domain chatbot
Recipes for building an open-domain chatbot
Stephen Roller
Emily Dinan
Naman Goyal
Da Ju
Mary Williamson
...
Myle Ott
Kurt Shuster
Eric Michael Smith
Y-Lan Boureau
Jason Weston
ALM
123
1,014
0
28 Apr 2020
Calibration of Pre-trained Transformers
Calibration of Pre-trained Transformers
Shrey Desai
Greg Durrett
UQLM
296
301
0
17 Mar 2020
Exploring the Limits of Transfer Learning with a Unified Text-to-Text
  Transformer
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel
Noam M. Shazeer
Adam Roberts
Katherine Lee
Sharan Narang
Michael Matena
Yanqi Zhou
Wei Li
Peter J. Liu
AIMat
470
20,317
0
23 Oct 2019
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and
  lighter
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Victor Sanh
Lysandre Debut
Julien Chaumond
Thomas Wolf
255
7,547
0
02 Oct 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Yinhan Liu
Myle Ott
Naman Goyal
Jingfei Du
Mandar Joshi
Danqi Chen
Omer Levy
M. Lewis
Luke Zettlemoyer
Veselin Stoyanov
AIMat
677
24,541
0
26 Jul 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty
Using Pre-Training Can Improve Model Robustness and Uncertainty
Dan Hendrycks
Kimin Lee
Mantas Mazeika
NoLa
76
726
0
28 Jan 2019
CommonsenseQA: A Question Answering Challenge Targeting Commonsense
  Knowledge
CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge
Alon Talmor
Jonathan Herzig
Nicholas Lourie
Jonathan Berant
RALM
144
1,747
0
02 Nov 2018
Regularizing Neural Networks by Penalizing Confident Output
  Distributions
Regularizing Neural Networks by Penalizing Confident Output Distributions
Gabriel Pereyra
George Tucker
J. Chorowski
Lukasz Kaiser
Geoffrey E. Hinton
NoLa
165
1,141
0
23 Jan 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCVBDL
842
5,841
0
05 Dec 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples
  in Neural Networks
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Dan Hendrycks
Kevin Gimpel
UQCV
168
3,472
0
07 Oct 2016
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