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Learning to Cascade: Confidence Calibration for Improving the Accuracy
  and Computational Cost of Cascade Inference Systems

Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems

15 April 2021
Shohei Enomoto
Takeharu Eda
    UQCV
ArXivPDFHTML

Papers citing "Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems"

14 / 14 papers shown
Title
Task as Context Prompting for Accurate Medical Symptom Coding Using Large Language Models
Task as Context Prompting for Accurate Medical Symptom Coding Using Large Language Models
Chengyang He
Wenlong Zhang
Violet Chen
Yue Ning
Ping Wang
26
0
0
03 Apr 2025
I Know What I Don't Know: Improving Model Cascades Through Confidence Tuning
I Know What I Don't Know: Improving Model Cascades Through Confidence Tuning
Stephan Rabanser
Nathalie Rauschmayr
Achin Kulshrestha
Petra Poklukar
Wittawat Jitkrittum
Sean Augenstein
Congchao Wang
Federico Tombari
42
0
0
26 Feb 2025
Breaking the Ceiling of the LLM Community by Treating Token Generation
  as a Classification for Ensembling
Breaking the Ceiling of the LLM Community by Treating Token Generation as a Classification for Ensembling
Yao-Ching Yu
Chun-Chih Kuo
Ziqi Ye
Yu-Cheng Chang
Yueh-Se Li
48
9
0
18 Jun 2024
Finding the SWEET Spot: Analysis and Improvement of Adaptive Inference
  in Low Resource Settings
Finding the SWEET Spot: Analysis and Improvement of Adaptive Inference in Low Resource Settings
Daniel Rotem
Michael Hassid
Jonathan Mamou
Roy Schwartz
17
5
0
04 Jun 2023
Perception and Semantic Aware Regularization for Sequential Confidence
  Calibration
Perception and Semantic Aware Regularization for Sequential Confidence Calibration
Zhenghua Peng
Yuanmao Luo
Tianshui Chen
Keke Xu
Shuangping Huang
AI4TS
30
2
0
31 May 2023
QuickNets: Saving Training and Preventing Overconfidence in Early-Exit
  Neural Architectures
QuickNets: Saving Training and Preventing Overconfidence in Early-Exit Neural Architectures
Devdhar Patel
H. Siegelmann
OnRL
23
1
0
25 Dec 2022
Turbo: Opportunistic Enhancement for Edge Video Analytics
Turbo: Opportunistic Enhancement for Edge Video Analytics
Yan Lu
Shiqi Jiang
Ting Cao
Yuanchao Shu
34
30
0
29 Jun 2022
CLCNet: Rethinking of Ensemble Modeling with Classification Confidence
  Network
CLCNet: Rethinking of Ensemble Modeling with Classification Confidence Network
Yaodong Yu
S. Horng
16
0
0
19 May 2022
Confidence Calibration for Intent Detection via Hyperspherical Space and
  Rebalanced Accuracy-Uncertainty Loss
Confidence Calibration for Intent Detection via Hyperspherical Space and Rebalanced Accuracy-Uncertainty Loss
Yantao Gong
Cao Liu
Fan Yang
Xunliang Cai
Guanglu Wan
Jiansong Chen
Weipeng Zhang
Houfeng Wang
UQCV
19
2
0
17 Mar 2022
Hidden Heterogeneity: When to Choose Similarity-Based Calibration
Hidden Heterogeneity: When to Choose Similarity-Based Calibration
K. Wagstaff
Thomas G. Dietterich
16
1
0
03 Feb 2022
Task-Oriented Communication for Multi-Device Cooperative Edge Inference
Task-Oriented Communication for Multi-Device Cooperative Edge Inference
Jiawei Shao
Yuyi Mao
Jun Zhang
20
128
0
01 Sep 2021
CascadeBERT: Accelerating Inference of Pre-trained Language Models via
  Calibrated Complete Models Cascade
CascadeBERT: Accelerating Inference of Pre-trained Language Models via Calibrated Complete Models Cascade
Lei Li
Yankai Lin
Deli Chen
Shuhuai Ren
Peng Li
Jie Zhou
Xu Sun
29
51
0
29 Dec 2020
Robust Out-of-distribution Detection for Neural Networks
Robust Out-of-distribution Detection for Neural Networks
Jiefeng Chen
Yixuan Li
Xi Wu
Yingyu Liang
S. Jha
OODD
161
84
0
21 Mar 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
950
20,567
0
17 Apr 2017
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