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Generating with Confidence: Uncertainty Quantification for Black-box
  Large Language Models

Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models

30 May 2023
Zhen Lin
Shubhendu Trivedi
Jimeng Sun
    HILM
ArXivPDFHTML

Papers citing "Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models"

28 / 28 papers shown
Title
Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding
Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding
Trilok Padhi
R. Kaur
Adam D. Cobb
Manoj Acharya
Anirban Roy
Colin Samplawski
Brian Matejek
Alexander M. Berenbeim
Nathaniel D. Bastian
Susmit Jha
20
0
0
30 Apr 2025
Uncertainty Quantification for Language Models: A Suite of Black-Box, White-Box, LLM Judge, and Ensemble Scorers
Uncertainty Quantification for Language Models: A Suite of Black-Box, White-Box, LLM Judge, and Ensemble Scorers
Dylan Bouchard
Mohit Singh Chauhan
HILM
70
0
0
27 Apr 2025
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
79
0
0
25 Apr 2025
Data-Driven Calibration of Prediction Sets in Large Vision-Language Models Based on Inductive Conformal Prediction
Data-Driven Calibration of Prediction Sets in Large Vision-Language Models Based on Inductive Conformal Prediction
Yuanchang Ye
Weiyan Wen
VLM
56
0
0
24 Apr 2025
TruthPrInt: Mitigating LVLM Object Hallucination Via Latent Truthful-Guided Pre-Intervention
TruthPrInt: Mitigating LVLM Object Hallucination Via Latent Truthful-Guided Pre-Intervention
Jinhao Duan
Fei Kong
Hao-Ran Cheng
James Diffenderfer
B. Kailkhura
Lichao Sun
Xiaofeng Zhu
Xiaoshuang Shi
Kaidi Xu
62
0
0
13 Mar 2025
Semantic Volume: Quantifying and Detecting both External and Internal Uncertainty in LLMs
Semantic Volume: Quantifying and Detecting both External and Internal Uncertainty in LLMs
Xiaomin Li
Zhou Yu
Ziji Zhang
Yingying Zhuang
S.
Narayanan Sadagopan
Anurag Beniwal
HILM
56
0
0
28 Feb 2025
Monte Carlo Temperature: a robust sampling strategy for LLM's uncertainty quantification methods
Monte Carlo Temperature: a robust sampling strategy for LLM's uncertainty quantification methods
Nicola Cecere
Andrea Bacciu
Ignacio Fernández Tobías
Amin Mantrach
61
1
0
25 Feb 2025
Large Language Model Confidence Estimation via Black-Box Access
Large Language Model Confidence Estimation via Black-Box Access
Tejaswini Pedapati
Amit Dhurandhar
Soumya Ghosh
Soham Dan
P. Sattigeri
84
3
0
21 Feb 2025
Cost-Saving LLM Cascades with Early Abstention
Cost-Saving LLM Cascades with Early Abstention
Michael J. Zellinger
Rex Liu
Matt Thomson
98
0
0
13 Feb 2025
Latent Space Chain-of-Embedding Enables Output-free LLM Self-Evaluation
Latent Space Chain-of-Embedding Enables Output-free LLM Self-Evaluation
Yiming Wang
Pei Zhang
Baosong Yang
Derek F. Wong
Rui-cang Wang
LRM
40
4
0
17 Oct 2024
TrustNavGPT: Modeling Uncertainty to Improve Trustworthiness of
  Audio-Guided LLM-Based Robot Navigation
TrustNavGPT: Modeling Uncertainty to Improve Trustworthiness of Audio-Guided LLM-Based Robot Navigation
Xingpeng Sun
Yiran Zhang
Xindi Tang
Amrit Singh Bedi
Aniket Bera
40
4
0
03 Aug 2024
Cost-Effective Hallucination Detection for LLMs
Cost-Effective Hallucination Detection for LLMs
Simon Valentin
Jinmiao Fu
Gianluca Detommaso
Shaoyuan Xu
Giovanni Zappella
Bryan Wang
HILM
33
4
0
31 Jul 2024
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph
Roman Vashurin
Ekaterina Fadeeva
Artem Vazhentsev
Akim Tsvigun
Daniil Vasilev
...
Timothy Baldwin
Timothy Baldwin
Maxim Panov
Artem Shelmanov
Artem Shelmanov
HILM
59
7
0
21 Jun 2024
CSS: Contrastive Semantic Similarity for Uncertainty Quantification of
  LLMs
CSS: Contrastive Semantic Similarity for Uncertainty Quantification of LLMs
Shuang Ao
Stefan Rueger
Advaith Siddharthan
23
1
0
05 Jun 2024
BIRD: A Trustworthy Bayesian Inference Framework for Large Language Models
BIRD: A Trustworthy Bayesian Inference Framework for Large Language Models
Yu Feng
Ben Zhou
Weidong Lin
Dan Roth
56
4
0
18 Apr 2024
Confidence Calibration and Rationalization for LLMs via Multi-Agent
  Deliberation
Confidence Calibration and Rationalization for LLMs via Multi-Agent Deliberation
Ruixin Yang
Dheeraj Rajagopal
S. Hayati
Bin Hu
Dongyeop Kang
LLMAG
30
3
0
14 Apr 2024
Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path
  Forward
Online Safety Analysis for LLMs: a Benchmark, an Assessment, and a Path Forward
Xuan Xie
Jiayang Song
Zhehua Zhou
Yuheng Huang
Da Song
Lei Ma
OffRL
35
6
0
12 Apr 2024
Multicalibration for Confidence Scoring in LLMs
Multicalibration for Confidence Scoring in LLMs
Gianluca Detommaso
Martín Bertrán
Riccardo Fogliato
Aaron Roth
24
12
0
06 Apr 2024
Methods to Estimate Large Language Model Confidence
Methods to Estimate Large Language Model Confidence
Maia Kotelanski
Robert Gallo
Ashwin Nayak
Thomas Savage
LM&MA
16
6
0
28 Nov 2023
Post-Abstention: Towards Reliably Re-Attempting the Abstained Instances
  in QA
Post-Abstention: Towards Reliably Re-Attempting the Abstained Instances in QA
Neeraj Varshney
Chitta Baral
31
13
0
02 May 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
64
92
0
30 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
51
30
0
25 May 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Jason W. Wei
Xuezhi Wang
Dale Schuurmans
Maarten Bosma
Brian Ichter
F. Xia
Ed H. Chi
Quoc Le
Denny Zhou
LM&Ro
LRM
AI4CE
ReLM
315
8,261
0
28 Jan 2022
DEUP: Direct Epistemic Uncertainty Prediction
DEUP: Direct Epistemic Uncertainty Prediction
Salem Lahlou
Moksh Jain
Hadi Nekoei
V. Butoi
Paul Bertin
Jarrid Rector-Brooks
Maksym Korablyov
Yoshua Bengio
PER
UQLM
UQCV
UD
195
80
0
16 Feb 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
197
152
0
30 Dec 2020
Calibration of Pre-trained Transformers
Calibration of Pre-trained Transformers
Shrey Desai
Greg Durrett
UQLM
234
288
0
17 Mar 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,635
0
05 Dec 2016
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
247
9,042
0
06 Jun 2015
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