2025 "few-shot learning" Papers

21 papers found

Are Transformers Able to Reason by Connecting Separated Knowledge in Training Data?

Yutong Yin, Zhaoran Wang

ICLR 2025posterarXiv:2501.15857
2
citations

Can LLMs Understand Time Series Anomalies?

Zihao Zhou, Rose Yu

ICLR 2025posterarXiv:2410.05440
32
citations

CapeX: Category-Agnostic Pose Estimation from Textual Point Explanation

Matan Rusanovsky, Or Hirschorn, Shai Avidan

ICLR 2025posterarXiv:2406.00384
8
citations

Causal Disentanglement and Cross-Modal Alignment for Enhanced Few-Shot Learning

Tianjiao Jiang, Zhen Zhang, Yuhang Liu et al.

ICCV 2025posterarXiv:2508.03102
1
citations

DETree: DEtecting Human-AI Collaborative Texts via Tree-Structured Hierarchical Representation Learning

Yongxin He, Shan Zhang, Yixuan Cao et al.

NeurIPS 2025poster
1
citations

Federated Few-Shot Class-Incremental Learning

Muhammad Anwar Masum, Mahardhika Pratama, Lin Liu et al.

ICLR 2025poster

Few-Shot Image Quality Assessment via Adaptation of Vision-Language Models

Xudong Li, Zihao Huang, Yan Zhang et al.

ICCV 2025posterarXiv:2409.05381
2
citations

Logits DeConfusion with CLIP for Few-Shot Learning

Shuo Li, Fang Liu, Zehua Hao et al.

CVPR 2025posterarXiv:2504.12104
6
citations

Meta-Dynamical State Space Models for Integrative Neural Data Analysis

Ayesha Vermani, Josue Nassar, Hyungju Jeon et al.

ICLR 2025posterarXiv:2410.05454

MoEMeta: Mixture-of-Experts Meta Learning for Few-Shot Relational Learning

Han Wu, Jie Yin

NeurIPS 2025posterarXiv:2510.23013

Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentation

Zhaochong An, Guolei Sun, Yun Liu et al.

ICLR 2025posterarXiv:2410.22489
22
citations

PAL: Sample-Efficient Personalized Reward Modeling for Pluralistic Alignment

Daiwei Chen, Yi Chen, Aniket Rege et al.

ICLR 2025poster
9
citations

Personalized Representation from Personalized Generation

Shobhita Sundaram, Julia Chae, Yonglong Tian et al.

ICLR 2025posterarXiv:2412.16156
4
citations

Preference-driven Knowledge Distillation for Few-shot Node Classification

Xing Wei, Chunchun Chen, Rui Fan et al.

NeurIPS 2025posterarXiv:2510.10116

Prompting as Scientific Inquiry

Ari Holtzman, Chenhao Tan

NeurIPS 2025oralarXiv:2507.00163

Self-Ensembling Gaussian Splatting for Few-Shot Novel View Synthesis

Chen Zhao, Xuan Wang, Tong Zhang et al.

ICCV 2025posterarXiv:2411.00144
3
citations

Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning

Achleshwar Luthra, Tianbao Yang, Tomer Galanti

NeurIPS 2025posterarXiv:2506.04411
1
citations

Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning

Juntae Lee, Munawar Hayat, Sungrack Yun

CVPR 2025posterarXiv:2506.15720
2
citations

UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection

Zhaopeng Gu, Bingke Zhu, Guibo Zhu et al.

CVPR 2025posterarXiv:2412.03342
22
citations

Weak-shot Keypoint Estimation via Keyness and Correspondence Transfer

Junjie Chen, Zeyu Luo, Zezheng Liu et al.

NeurIPS 2025poster

Why In-Context Learning Models are Good Few-Shot Learners?

Shiguang Wu, Yaqing Wang, Quanming Yao

ICLR 2025poster