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To Believe or Not to Believe Your LLM

To Believe or Not to Believe Your LLM

4 June 2024
Yasin Abbasi-Yadkori
Ilja Kuzborskij
András György
Csaba Szepesvári
    UQCV
ArXivPDFHTML

Papers citing "To Believe or Not to Believe Your LLM"

16 / 16 papers shown
Title
Do Large Language Models (Really) Need Statistical Foundations?
Do Large Language Models (Really) Need Statistical Foundations?
Weijie Su
208
0
0
25 May 2025
If Concept Bottlenecks are the Question, are Foundation Models the Answer?
If Concept Bottlenecks are the Question, are Foundation Models the Answer?
Nicola Debole
Pietro Barbiero
Francesco Giannini
Andrea Passerini
Stefano Teso
Emanuele Marconato
410
1
0
28 Apr 2025
Do We Truly Need So Many Samples? Multi-LLM Repeated Sampling Efficiently Scales Test-Time Compute
Do We Truly Need So Many Samples? Multi-LLM Repeated Sampling Efficiently Scales Test-Time Compute
Jianhao Chen
Zishuo Xun
Bocheng Zhou
Han Qi
Qiaosheng Zhang
...
Wei Hu
Yuzhong Qu
W. Ouyang
Wanli Ouyang
Shuyue Hu
109
2
0
01 Apr 2025
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
Yibin Wang
Haizhou Shi
Ligong Han
Dimitris N. Metaxas
Hao Wang
BDL
UQLM
172
9
0
28 Jan 2025
Training-Free Bayesianization for Low-Rank Adapters of Large Language Models
Training-Free Bayesianization for Low-Rank Adapters of Large Language Models
Haizhou Shi
Yibin Wang
Ligong Han
Huatian Zhang
Hao Wang
UQCV
162
2
0
07 Dec 2024
What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering
What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering
Federico Errica
G. Siracusano
D. Sanvito
Roberto Bifulco
135
25
0
18 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
121
5
0
18 Apr 2024
Mitigating LLM Hallucinations via Conformal Abstention
Mitigating LLM Hallucinations via Conformal Abstention
Yasin Abbasi-Yadkori
Ilja Kuzborskij
David Stutz
András György
Adam Fisch
...
Wei-Hung Weng
Yao-Yuan Yang
Csaba Szepesvári
A. Cemgil
Nenad Tomašev
HILM
67
18
0
04 Apr 2024
Discovering Latent Knowledge in Language Models Without Supervision
Discovering Latent Knowledge in Language Models Without Supervision
Collin Burns
Haotian Ye
Dan Klein
Jacob Steinhardt
122
363
0
07 Dec 2022
Large Language Models with Controllable Working Memory
Large Language Models with Controllable Working Memory
Daliang Li
A. S. Rawat
Manzil Zaheer
Xin Wang
Michal Lukasik
Andreas Veit
Felix X. Yu
Surinder Kumar
KELM
106
169
0
09 Nov 2022
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and
  Bootstrapping
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping
Vikranth Dwaracherla
Zheng Wen
Ian Osband
Xiuyuan Lu
S. Asghari
Benjamin Van Roy
UQCV
71
20
0
08 Jun 2022
Selective Classification Via Neural Network Training Dynamics
Selective Classification Via Neural Network Training Dynamics
Stephan Rabanser
Anvith Thudi
Kimia Hamidieh
Adam Dziedzic
Nicolas Papernot
66
22
0
26 May 2022
Entity-Based Knowledge Conflicts in Question Answering
Entity-Based Knowledge Conflicts in Question Answering
Shayne Longpre
Kartik Perisetla
Anthony Chen
Nikhil Ramesh
Chris DuBois
Sameer Singh
HILM
318
257
0
10 Sep 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
242
167
0
30 Dec 2020
Depth Uncertainty in Neural Networks
Depth Uncertainty in Neural Networks
Javier Antorán
J. Allingham
José Miguel Hernández-Lobato
UQCV
OOD
BDL
67
101
0
15 Jun 2020
TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for
  Reading Comprehension
TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
Mandar Joshi
Eunsol Choi
Daniel S. Weld
Luke Zettlemoyer
RALM
195
2,636
0
09 May 2017
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