Paper "few-shot learning" Papers
43 papers found
Conference
A Stochastic Approach to Bi-Level Optimization for Hyperparameter Optimization and Meta Learning
Minyoung Kim, Timothy Hospedales
Bridging Molecular Graphs and Large Language Models
Runze Wang, Mingqi Yang, Yanming Shen
ConceptSearch: Towards Efficient Program Search Using LLMs for Abstraction and Reasoning Corpus (ARC)
Kartik Singhal, Gautam Shroff
Core Knowledge Learning Framework for Graph
Bowen Zhang, Zhichao Huang, Guangning Xu et al.
DiffCLIP: Few-shot Language-driven Multimodal Classifier
Jiaqing Zhang, Mingxiang Cao, Xue Yang et al.
Enhancing Generalized Few-Shot Semantic Segmentation via Effective Knowledge Transfer
Xinyue Chen, Miaojing Shi, Zijian Zhou et al.
Enhancing Masked Time-Series Modeling via Dropping Patches
Tianyu Qiu, Yi Xie, Hao Niu et al.
Envisioning Class Entity Reasoning by Large Language Models for Few-shot Learning
Mushui Liu, Fangtai Wu, Bozheng Li et al.
FAMNet: Frequency-aware Matching Network for Cross-domain Few-shot Medical Image Segmentation
Yuntian Bo, Yazhou Zhu, Lunbo Li et al.
Few-Shot Domain Adaptation for Learned Image Compression
Tianyu Zhang, Haotian Zhang, Yuqi Li et al.
Few-Shot, No Problem: Descriptive Continual Relation Extraction
Nguyen Xuan Thanh, Anh Duc Le, Quyen Tran et al.
HeGTa: Leveraging Heterogeneous Graph-enhanced Large Language Models for Few-shot Complex Table Understanding
Rihui Jin, Yu Li, Guilin Qi et al.
HEP-NAS: Towards Efficient Few-shot Neural Architecture Search via Hierarchical Edge Partitioning
Jianfeng Li, Jiawen Zhang, Feng Wang et al.
Holistic Semantic Representation for Navigational Trajectory Generation
Ji Cao, Tongya Zheng, Qinghong Guo et al.
Multi-Modal Grounded Planning and Efficient Replanning for Learning Embodied Agents with a Few Examples
Taewoong Kim, Byeonghwi Kim, Jonghyun Choi
Neural Conformal Control for Time Series Forecasting
Ruipu Li, Alexander Rodríguez
Normalize Then Propagate: Efficient Homophilous Regularization for Few-Shot Semi-Supervised Node Classification
Baoming Zhang, MingCai Chen, Jianqing Song et al.
Revisiting Multimodal Fusion for 3D Anomaly Detection from an Architectural Perspective
Kaifang Long, Guoyang Xie, Lianbo Ma et al.
Text and Image Are Mutually Beneficial: Enhancing Training-Free Few-Shot Classification with CLIP
Yayuan Li, Jintao Guo, Lei Qi et al.
TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts
Yu-Hao Huang, Chang Xu, Yueying Wu et al.
AE-NeRF: Audio Enhanced Neural Radiance Field for Few Shot Talking Head Synthesis
Dongze Li, Kang Zhao, Wei Wang 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.
BDIQA: A New Dataset for Video Question Answering to Explore Cognitive Reasoning through Theory of Mind
Yuanyuan Mao, Xin Lin, Qin Ni et al.
Code-Style In-Context Learning for Knowledge-Based Question Answering
Zhijie Nie, Richong Zhang, Zhongyuan Wang et al.
Dialogue for Prompting: A Policy-Gradient-Based Discrete Prompt Generation for Few-Shot Learning
Chengzhengxu Li, Xiaoming Liu, Yichen Wang et al.
Does Few-Shot Learning Suffer from Backdoor Attacks?
Xinwei Liu, Xiaojun Jia, Jindong Gu et al.
Few-Shot Learning from Augmented Label-Uncertain Queries in Bongard-HOI
Qinqian Lei, Bo Wang, Robby T. Tan
Few-Shot Neural Radiance Fields under Unconstrained Illumination
SeokYeong Lee, JunYong Choi, Seungryong Kim et al.
FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering
Zhenyu Li, Sunqi Fan, Yu Gu et al.
H-ensemble: An Information Theoretic Approach to Reliable Few-Shot Multi-Source-Free Transfer
Yanru Wu, Jianning Wang, Weida Wang et al.
HGPrompt: Bridging Homogeneous and Heterogeneous Graphs for Few-Shot Prompt Learning
Xingtong Yu, Yuan Fang, Zemin Liu et al.
LAMM: Label Alignment for Multi-Modal Prompt Learning
Jingsheng Gao, Jiacheng Ruan, Suncheng Xiang et al.
Make Prompts Adaptable: Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior
Youngjae Cho, HeeSun Bae, Seungjae Shin et al.
MathAttack: Attacking Large Language Models towards Math Solving Ability
Zihao Zhou, Qiufeng Wang, Mingyu Jin et al.
MetaDiff: Meta-Learning with Conditional Diffusion for Few-Shot Learning
Baoquan Zhang, Chuyao Luo, Demin Yu et al.
Prompting Segmentation with Sound Is Generalizable Audio-Visual Source Localizer
Yaoting Wang, Liu Weisong, Guangyao Li et al.
Robust Few-Shot Named Entity Recognition with Boundary Discrimination and Correlation Purification
Xiaojun Xue, Chunxia Zhang, Tianxiang Xu et al.
Task Contamination: Language Models May Not Be Few-Shot Anymore
Changmao Li, Jeffrey Flanigan
Vision Transformer Off-the-Shelf: A Surprising Baseline for Few-Shot Class-Agnostic Counting
Zhicheng Wang, Liwen Xiao, Zhiguo Cao et al.
Weak Distribution Detectors Lead to Stronger Generalizability of Vision-Language Prompt Tuning
Kun Ding, Haojian Zhang, Qiang Yu et al.