Poster "few-shot learning" Papers
46 papers found
Are Transformers Able to Reason by Connecting Separated Knowledge in Training Data?
Yutong Yin, Zhaoran Wang
Can LLMs Understand Time Series Anomalies?
Zihao Zhou, Rose Yu
CapeX: Category-Agnostic Pose Estimation from Textual Point Explanation
Matan Rusanovsky, Or Hirschorn, Shai Avidan
Causal Disentanglement and Cross-Modal Alignment for Enhanced Few-Shot Learning
Tianjiao Jiang, Zhen Zhang, Yuhang Liu et al.
DETree: DEtecting Human-AI Collaborative Texts via Tree-Structured Hierarchical Representation Learning
Yongxin He, Shan Zhang, Yixuan Cao et al.
Doctor Approved: Generating Medically Accurate Skin Disease Images through AI-Expert Feedback
Janet Wang, Yunbei Zhang, Zhengming Ding et al.
Federated Few-Shot Class-Incremental Learning
Muhammad Anwar Masum, Mahardhika Pratama, Lin Liu et al.
Few-Shot Image Quality Assessment via Adaptation of Vision-Language Models
Xudong Li, Zihao Huang, Yan Zhang et al.
Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language Model
Zhaochong An, Guolei Sun, Yun Liu et al.
Logits DeConfusion with CLIP for Few-Shot Learning
Shuo Li, Fang Liu, Zehua Hao et al.
Meta-Dynamical State Space Models for Integrative Neural Data Analysis
Ayesha Vermani, Josue Nassar, Hyungju Jeon et al.
MoEMeta: Mixture-of-Experts Meta Learning for Few-Shot Relational Learning
Han Wu, Jie Yin
Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentation
Zhaochong An, Guolei Sun, Yun Liu et al.
PAL: Sample-Efficient Personalized Reward Modeling for Pluralistic Alignment
Daiwei Chen, Yi Chen, Aniket Rege et al.
Personalized Representation from Personalized Generation
Shobhita Sundaram, Julia Chae, Yonglong Tian et al.
Preference-driven Knowledge Distillation for Few-shot Node Classification
Xing Wei, Chunchun Chen, Rui Fan et al.
Self-Ensembling Gaussian Splatting for Few-Shot Novel View Synthesis
Chen Zhao, Xuan Wang, Tong Zhang et al.
Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
Achleshwar Luthra, Tianbao Yang, Tomer Galanti
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.
Unveiling the Learning Mind of Language Models: A Cognitive Framework and Empirical Study
Zhengyu Hu, Jianxun Lian, Zheyuan Xiao 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
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.
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
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.
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.
Enabling Few-Shot Learning with PID Control: A Layer Adaptive Optimizer
Le Yu, Xinde Li, Pengfei Zhang 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 Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind
Mo Yu, Qiujing Wang, Shunchi Zhang et al.
Few-shot NeRF by Adaptive Rendering Loss Regularization
Qingshan Xu, Xuanyu Yi, Jianyao Xu et al.
Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries
Amine Ouasfi, Adnane Boukhayma
GPSFormer: A Global Perception and Local Structure Fitting-based Transformer for Point Cloud Understanding
Changshuo Wang, Meiqing Wu, Siew-Kei Lam et al.
In-Context Unlearning: Language Models as Few-Shot Unlearners
Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju
LangCell: Language-Cell Pre-training for Cell Identity Understanding
Suyuan Zhao, Jiahuan Zhang, Yushuai Wu et al.
Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning
Sungwon Han, Jinsung Yoon, Sercan Arik et al.
On the Approximation Risk of Few-Shot Class-Incremental Learning
Xuan Wang, Zhong Ji, Xiyao Liu et al.
Propose, Assess, Search: Harnessing LLMs for Goal-Oriented Planning in Instructional Videos
Mohaiminul Islam, Tushar Nagarajan, Huiyu Wang et al.
Recursive Visual Programming
Jiaxin Ge, Sanjay Subramanian, Baifeng Shi et al.