Poster "data augmentation" Papers

18 papers found

A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics

Licong Lin, Song Mei

NeurIPS 2025posterarXiv:2503.17538
3
citations

HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models

Seanie Lee, Haebin Seong, Dong Bok Lee et al.

ICLR 2025posterarXiv:2410.01524
13
citations

TaiwanVQA: Benchmarking and Enhancing Cultural Understanding in Vision-Language Models

Hsin Yi Hsieh, Shang-Wei Liu, Chang-Chih Meng et al.

NeurIPS 2025poster

Truth over Tricks: Measuring and Mitigating Shortcut Learning in Misinformation Detection

Herun Wan, Jiaying Wu, Minnan Luo et al.

NeurIPS 2025posterarXiv:2506.02350
6
citations

What Do Latent Action Models Actually Learn?

Chuheng Zhang, Tim Pearce, Pushi Zhang et al.

NeurIPS 2025posterarXiv:2506.15691
7
citations

ATraDiff: Accelerating Online Reinforcement Learning with Imaginary Trajectories

Qianlan Yang, Yu-Xiong Wang

ICML 2024poster

CLAP: Isolating Content from Style through Contrastive Learning with Augmented Prompts

Yichao Cai, Yuhang Liu, Zhen Zhang et al.

ECCV 2024posterarXiv:2311.16445
11
citations

Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation

Yididiya Nadew, Xuhui Fan, Christopher J Quinn

ICML 2024poster

DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation

Zelin Zang, Hao Luo, Kai Wang et al.

ICML 2024poster

DiffStitch: Boosting Offline Reinforcement Learning with Diffusion-based Trajectory Stitching

Guanghe Li, Yixiang Shan, Zhengbang Zhu et al.

ICML 2024poster

Emergent Equivariance in Deep Ensembles

Jan Gerken, Pan Kessel

ICML 2024poster

EquiAV: Leveraging Equivariance for Audio-Visual Contrastive Learning

Jongsuk Kim, Hyeongkeun Lee, Kyeongha Rho et al.

ICML 2024poster

First-Order Manifold Data Augmentation for Regression Learning

Ilya Kaufman, Omri Azencot

ICML 2024poster

Image-Feature Weak-to-Strong Consistency: An Enhanced Paradigm for Semi-Supervised Learning

Zhiyu Wu, Jin shi Cui

ECCV 2024posterarXiv:2408.12614
1
citations

Improved Generalization of Weight Space Networks via Augmentations

Aviv Shamsian, Aviv Navon, David Zhang et al.

ICML 2024poster

Sample-Efficient Multiagent Reinforcement Learning with Reset Replay

Yaodong Yang, Guangyong Chen, Jianye Hao et al.

ICML 2024poster

Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup

Damien Teney, Jindong Wang, Ehsan Abbasnejad

ICML 2024poster

The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective

Chi-Heng Lin, Chiraag Kaushik, Eva Dyer et al.

ICML 2024poster