AAAI Paper "few-shot learning" Papers
23 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.
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.