Cover Image

Filtering with Confidence: When Data Augmentation Meets Conformal Prediction

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Zixuan, Jeong, So Won, Liu, Yating, Jung, Yeo Jin, Donnat, Claire
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SpeedCP: Fast Kernel-based Conditional Conformal Prediction
by: Liu, Yating, et al.
Published: (2025)

LOBSTUR: A Local Bootstrap Framework for Tuning Unsupervised Representations in Graph Neural Networks
by: Jeong, So Won, et al.
Published: (2025)

Graph Topic Modeling for Documents with Spatial or Covariate Dependencies
by: Jung, Yeo Jin, et al.
Published: (2024)

GNUMAP: A Parameter-Free Approach to Unsupervised Dimensionality Reduction via Graph Neural Networks
by: You, Jihee, et al.
Published: (2024)

Tensor Topic Modeling Via HOSVD
by: Liu, Yating, et al.
Published: (2024)

Confidence on the Focal: Conformal Prediction with Selection-Conditional Coverage
by: Jin, Ying, et al.
Published: (2024)

Joint learning of a network of linear dynamical systems via total variation penalization
by: Donnat, Claire, et al.
Published: (2025)

Conformal Prediction Meets Long-tail Classification
by: Liu, Shuqi, et al.
Published: (2025)

From Conformal Predictions to Confidence Regions
by: Guille-Escuret, Charles, et al.
Published: (2024)

Semi-Supervised Learning on Graphs using Graph Neural Networks
by: Chen, Juntong, et al.
Published: (2026)

From Small to Large Language Models: Revisiting the Federalist Papers
by: Jeong, So Won, et al.
Published: (2025)

When Dynamic Data Selection Meets Data Augmentation
by: Yang, Suorong, et al.
Published: (2025)

The Effects of Data Augmentation on Confidence Estimation for LLMs
by: Wang, Rui, et al.
Published: (2025)

Conditional Flow Matching for Bayesian Posterior Inference
by: Zhai, Percy S., et al.
Published: (2025)

On Training-Conditional Conformal Prediction and Binomial Proportion Confidence Intervals
by: Coppola, Rudi, et al.
Published: (2025)

Neural Optimal Transport Meets Multivariate Conformal Prediction
by: Kondratyev, Vladimir, et al.
Published: (2025)

Optimal Transport-based Conformal Prediction
by: Thurin, Gauthier, et al.
Published: (2025)

When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs
by: Jeong, Soyeong, et al.
Published: (2025)

Beyond Conformal Predictors: Adaptive Conformal Inference with Confidence Predictors
by: Szabadváry, Johan Hallberg, et al.
Published: (2024)

DistMatch: Adaptive Binning via Distribution Matching for Robust Sequential Conformal Prediction
by: Menadjiev, Enver, et al.
Published: (2026)

Robust Validation: Confident Predictions Even When Distributions Shift
by: Cauchois, Maxime, et al.
Published: (2020)

Conformal Calibration of Statistical Confidence Sets
by: Cabezas, Luben M. C., et al.
Published: (2024)

Conformal Prediction for Compositional Data
by: Amaral, Lucas P., et al.
Published: (2025)

Beyond Confidence: Adaptive Abstention in Dual-Threshold Conformal Prediction for Autonomous System Perception
by: Kumar, Divake, et al.
Published: (2025)

Efficient Canonical Correlation Analysis with Sparsity
by: Wu, Zixuan, et al.
Published: (2025)

Understanding the Effect of GCN Convolutions in Regression Tasks
by: Chen, Juntong, et al.
Published: (2024)

Knowing When to Answer: Adaptive Confidence Refinement for Reliable Audio-Visual Question Answering
by: Tran, Dinh Phu, et al.
Published: (2026)

Questioning the Coverage-Length Metric in Conformal Prediction: When Shorter Intervals Are Not Better
by: Min, Yizhou, et al.
Published: (2026)

Time-Frequency Filtering Meets Graph Clustering
by: Colominas, Marcelo A., et al.
Published: (2025)

When to Trust Your Data: Enhancing Dyna-Style Model-Based Reinforcement Learning With Data Filter
by: Li, Yansong, et al.
Published: (2024)

Multi-Distribution Robust Conformal Prediction
by: Yang, Yuqi, et al.
Published: (2026)

When Noisy Labels Meet Class Imbalance on Graphs: A Graph Augmentation Method with LLM and Pseudo Label
by: Xia, Riting, et al.
Published: (2025)

Conformal Alignment: Knowing When to Trust Foundation Models with Guarantees
by: Gui, Yu, et al.
Published: (2024)

When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
by: Zhang, Biao, et al.
Published: (2024)

Split Conformal Prediction under Data Contamination
by: Clarkson, Jase, et al.
Published: (2024)

Efficient Conformal Prediction under Data Heterogeneity
by: Plassier, Vincent, et al.
Published: (2023)

AnoF-Diff: One-Step Diffusion-Based Anomaly Detection for Forceful Tool Use
by: Lin, Yating, et al.
Published: (2025)

When Does Confidence-Based Cascade Deferral Suffice?
by: Jitkrittum, Wittawat, et al.
Published: (2023)

Conformal Prediction for Class-wise Coverage via Augmented Label Rank Calibration
by: Shi, Yuanjie, et al.
Published: (2024)

When Machine Learning Gets Personal: Evaluating Prediction and Explanation
by: Cornelis, Louisa, et al.
Published: (2025)