ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2402.17124
  4. Cited By
Fact-and-Reflection (FaR) Improves Confidence Calibration of Large
  Language Models

Fact-and-Reflection (FaR) Improves Confidence Calibration of Large Language Models

27 February 2024
Xinran Zhao
Hongming Zhang
Xiaoman Pan
Wenlin Yao
Dong Yu
Tongshuang Wu
Jianshu Chen
    HILM
    LRM
ArXivPDFHTML

Papers citing "Fact-and-Reflection (FaR) Improves Confidence Calibration of Large Language Models"

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
Cycles of Thought: Measuring LLM Confidence through Stable Explanations
Cycles of Thought: Measuring LLM Confidence through Stable Explanations
Evan Becker
Stefano Soatto
45
6
0
05 Jun 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
78
44
0
22 May 2023
In-context Learning and Induction Heads
In-context Learning and Induction Heads
Catherine Olsson
Nelson Elhage
Neel Nanda
Nicholas Joseph
Nova Dassarma
...
Tom B. Brown
Jack Clark
Jared Kaplan
Sam McCandlish
C. Olah
250
463
0
24 Sep 2022
Re-Examining Calibration: The Case of Question Answering
Re-Examining Calibration: The Case of Question Answering
Chenglei Si
Chen Zhao
Sewon Min
Jordan L. Boyd-Graber
64
30
0
25 May 2022
Large Language Models are Zero-Shot Reasoners
Large Language Models are Zero-Shot Reasoners
Takeshi Kojima
S. Gu
Machel Reid
Yutaka Matsuo
Yusuke Iwasawa
ReLM
LRM
328
4,077
0
24 May 2022
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Xuezhi Wang
Jason W. Wei
Dale Schuurmans
Quoc Le
Ed H. Chi
Sharan Narang
Aakanksha Chowdhery
Denny Zhou
ReLM
BDL
LRM
AI4CE
314
3,273
0
21 Mar 2022
Training language models to follow instructions with human feedback
Training language models to follow instructions with human feedback
Long Ouyang
Jeff Wu
Xu Jiang
Diogo Almeida
Carroll L. Wainwright
...
Amanda Askell
Peter Welinder
Paul Christiano
Jan Leike
Ryan J. Lowe
OSLM
ALM
339
12,003
0
04 Mar 2022
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit
  Reasoning Strategies
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies
Mor Geva
Daniel Khashabi
Elad Segal
Tushar Khot
Dan Roth
Jonathan Berant
RALM
250
677
0
06 Jan 2021
Calibration of Pre-trained Transformers
Calibration of Pre-trained Transformers
Shrey Desai
Greg Durrett
UQLM
243
290
0
17 Mar 2020
1