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Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive
  Batch Selection
v1v2 (latest)

Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch Selection

International Conference on Information and Knowledge Management (CIKM), 2019
19 November 2019
Hwanjun Song
Minseok Kim
Sundong Kim
Jae-Gil Lee
ArXiv (abs)PDFHTML

Papers citing "Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch Selection"

8 / 8 papers shown
Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay
Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay
Yifan Sun
Jingyan Shen
Yibin Wang
Tianyu Chen
Zhendong Wang
Mingyuan Zhou
Huan Zhang
623
31
0
05 Jun 2025
Batch Selection for Multi-Label Classification Guided by Uncertainty and
  Dynamic Label Correlations
Batch Selection for Multi-Label Classification Guided by Uncertainty and Dynamic Label CorrelationsAAAI Conference on Artificial Intelligence (AAAI), 2024
Ao Zhou
Yinan Han
Jin Wang
Grigorios Tsoumakas
UQCV
448
1
0
21 Dec 2024
Rho-1: Not All Tokens Are What You Need
Rho-1: Not All Tokens Are What You Need
Zheng-Wen Lin
Zhibin Gou
Yeyun Gong
Xiao Liu
Haoran Pan
...
Chen Lin
Yujiu Yang
Jian Jiao
Nan Duan
Weizhu Chen
CLL
480
123
0
11 Apr 2024
Multi-Label Adaptive Batch Selection by Highlighting Hard and Imbalanced
  Samples
Multi-Label Adaptive Batch Selection by Highlighting Hard and Imbalanced Samples
Ao Zhou
Yinan Han
Jin Wang
Grigorios Tsoumakas
419
3
0
27 Mar 2024
Bandit-Driven Batch Selection for Robust Learning under Label Noise
Bandit-Driven Batch Selection for Robust Learning under Label Noise
Michal Lisicki
Mihai Nica
Graham W. Taylor
398
1
0
31 Oct 2023
Improve Deep Image Inpainting by Emphasizing the Complexity of Missing
  Regions
Improve Deep Image Inpainting by Emphasizing the Complexity of Missing Regions
Yufeng Wang
Dan Li
Cong Xu
Min Yang
110
0
0
13 Feb 2022
Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity
  and Few-Shot Difficulty
Understanding Cross-Domain Few-Shot Learning Based on Domain Similarity and Few-Shot DifficultyNeural Information Processing Systems (NeurIPS), 2022
Jaehoon Oh
Sungnyun Kim
Namgyu Ho
Jin-Hwa Kim
Hwanjun Song
Se-Young Yun
335
61
0
01 Feb 2022
Active Learning for Human-in-the-Loop Customs Inspection
Active Learning for Human-in-the-Loop Customs InspectionIEEE Transactions on Knowledge and Data Engineering (TKDE), 2020
Sundong Kim
Tung Mai
Sungwon Han
Sungwon Park
Thien Khanh
Jaechan So
Karandeep Singh
M. Cha
372
11
0
27 Oct 2020
1
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