"few-shot learning" Papers
136 papers found • Page 2 of 3
Conference
Self-Ensembling Gaussian Splatting for Few-Shot Novel View Synthesis
Chen Zhao, Xuan Wang, Tong Zhang et al.
Self-Evolving Visual Concept Library using Vision-Language Critics
Atharva Sehgal, Patrick Yuan, Ziniu Hu et al.
Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
Achleshwar Luthra, Tianbao Yang, Tomer Galanti
Support Vector Generation: Kernelizing Large Language Models for Efficient Zero‑Shot NLP
Shohei Ohsawa
Test-Time Visual In-Context Tuning
Jiahao Xie, Alessio Tonioni, Nathalie Rauschmayr et al.
Text and Image Are Mutually Beneficial: Enhancing Training-Free Few-Shot Classification with CLIP
Yayuan Li, Jintao Guo, Lei Qi et al.
The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation
Yuhan Liu, Yixiong Zou, Yuhua Li et al.
TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts
Yu-Hao Huang, Chang Xu, Yueying Wu et al.
Time Series Generation Under Data Scarcity: A Unified Generative Modeling Approach
Tal Gonen, Itai Pemper, Ilan Naiman et al.
Tripartite Weight-Space Ensemble for Few-Shot Class-Incremental Learning
Juntae Lee, Munawar Hayat, Sungrack Yun
UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection
Zhaopeng Gu, Bingke Zhu, Guibo Zhu et al.
Universal Few-shot Spatial Control for Diffusion Models
Kiet Nguyen, Chanhyuk Lee, Donggyun Kim et al.
Unsupervised Meta-Learning via In-Context Learning
Anna Vettoruzzo, Lorenzo Braccaioli, Joaquin Vanschoren et al.
Unveiling the Learning Mind of Language Models: A Cognitive Framework and Empirical Study
Zhengyu Hu, Jianxun Lian, Zheyuan Xiao et al.
VaMP: Variational Multi-Modal Prompt Learning for Vision-Language Models
Silin Cheng, Kai Han
Verbalized Representation Learning for Interpretable Few-Shot Generalization
Cheng-Fu Yang, Da Yin, Wenbo Hu et al.
VT-FSL: Bridging Vision and Text with LLMs for Few-Shot Learning
Wenhao Li, Qiangchang Wang, Xianjing Meng et al.
Weak-shot Keypoint Estimation via Keyness and Correspondence Transfer
Junjie Chen, Zeyu Luo, Zezheng Liu et al.
Why In-Context Learning Models are Good Few-Shot Learners?
Shiguang Wu, Yaqing Wang, Quanming Yao
AE-NeRF: Audio Enhanced Neural Radiance Field for Few Shot Talking Head Synthesis
Dongze Li, Kang Zhao, Wei Wang et al.
A Graph-Based Approach for Category-Agnostic Pose Estimation
Or Hirschorn, Shai Avidan
Align Before Adapt: Leveraging Entity-to-Region Alignments for Generalizable Video Action Recognition
Yifei Chen, Dapeng Chen, Ruijin Liu et al.
Anchoring Path for Inductive Relation Prediction in Knowledge Graphs
Zhixiang Su, Di Wang, Chunyan Miao et al.
AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Model
Teng Hu, Jiangning Zhang, Ran Yi et al.
AnomalyGPT: Detecting Industrial Anomalies Using Large Vision-Language Models
Zhaopeng Gu, Bingke Zhu, Guibo Zhu et al.
Any-Way Meta Learning
JunHoo Lee, Yearim Kim, Hyunho Lee et al.
Are Synthetic Data Useful for Egocentric Hand-Object Interaction Detection?
Rosario Leonardi, Antonino Furnari, Francesco Ragusa et al.
Auctionformer: A Unified Deep Learning Algorithm for Solving Equilibrium Strategies in Auction Games
Kexin Huang, Ziqian Chen, xue wang et al.
Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities
Zhifeng Kong, ARUSHI GOEL, Rohan Badlani et al.
BDIQA: A New Dataset for Video Question Answering to Explore Cognitive Reasoning through Theory of Mind
Yuanyuan Mao, Xin Lin, Qin Ni et al.
Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models
Zhihe Lu, Jiawang Bai, Xin Li et al.
Byzantine Resilient and Fast Federated Few-Shot Learning
Ankit Pratap Singh, Namrata Vaswani
CLOSER: Towards Better Representation Learning for Few-Shot Class-Incremental Learning
Junghun Oh, Sungyong Baik, Kyoung Mu Lee
Code-Style In-Context Learning for Knowledge-Based Question Answering
Zhijie Nie, Richong Zhang, Zhongyuan Wang et al.
Compositional Few-Shot Class-Incremental Learning
Yixiong Zou, Shanghang Zhang, haichen zhou et al.
Conceptual Codebook Learning for Vision-Language Models
Yi Zhang, Ke Yu, Siqi Wu et al.
Context Diffusion: In-Context Aware Image Generation
Ivona Najdenkoska, Animesh Sinha, Abhimanyu Dubey et al.
DataDream: Few-shot Guided Dataset Generation
Jae Myung Kim, Jessica Bader, Stephan Alaniz et al.
DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection
Zhi Zhou, Ming Yang, Jiang-Xin Shi et al.
Dialogue for Prompting: A Policy-Gradient-Based Discrete Prompt Generation for Few-Shot Learning
Chengzhengxu Li, Xiaoming Liu, Yichen Wang et al.
DiffusionPen: Towards Controlling the Style of Handwritten Text Generation
KONSTANTINA NIKOLAIDOU, George Retsinas, Giorgos Sfikas et al.
Does Few-Shot Learning Suffer from Backdoor Attacks?
Xinwei Liu, Xiaojun Jia, Jindong Gu et al.
Enabling Few-Shot Learning with PID Control: A Layer Adaptive Optimizer
Le Yu, Xinde Li, Pengfei Zhang et al.
Enhance Image Classification via Inter-Class Image Mixup with Diffusion Model
Zhicai Wang, Longhui Wei, Tan Wang et al.
Exploring Active Learning in Meta-Learning: Enhancing Context Set Labeling
Wonho Bae, Jing Wang, Danica J. Sutherland
Exploring the LLM Journey from Cognition to Expression with Linear Representations
Yuzi Yan, Jialian Li, YipinZhang et al.
Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation
Guan Gui, Bin-Bin Gao, Jun Liu et al.
Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind
Mo Yu, Qiujing Wang, Shunchi Zhang et al.
Few-Shot Learning from Augmented Label-Uncertain Queries in Bongard-HOI
Qinqian Lei, Bo Wang, Robby T. Tan
Few-shot NeRF by Adaptive Rendering Loss Regularization
Qingshan Xu, Xuanyu Yi, Jianyao Xu et al.