2024 "few-shot learning" Papers
44 papers found
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.
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
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.
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.
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.
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 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.
Few-Shot Neural Radiance Fields under Unconstrained Illumination
SeokYeong Lee, JunYong Choi, Seungryong Kim et al.
Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries
Amine Ouasfi, Adnane Boukhayma
FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering
Zhenyu Li, Sunqi Fan, Yu Gu et al.
GPSFormer: A Global Perception and Local Structure Fitting-based Transformer for Point Cloud Understanding
Changshuo Wang, Meiqing Wu, Siew-Kei Lam 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.
In-Context Unlearning: Language Models as Few-Shot Unlearners
Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju
LAMM: Label Alignment for Multi-Modal Prompt Learning
Jingsheng Gao, Jiacheng Ruan, Suncheng Xiang et al.
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.
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.
One Meta-tuned Transformer is What You Need for Few-shot Learning
Xu Yang, Huaxiu Yao, Ying WEI
On the Approximation Risk of Few-Shot Class-Incremental Learning
Xuan Wang, Zhong Ji, Xiyao Liu et al.
Prompting Segmentation with Sound Is Generalizable Audio-Visual Source Localizer
Yaoting Wang, Liu Weisong, Guangyao Li et al.
Propose, Assess, Search: Harnessing LLMs for Goal-Oriented Planning in Instructional Videos
Mohaiminul Islam, Tushar Nagarajan, Huiyu Wang 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.