Summary of Non-negative Subspace Feature Representation For Few-shot Learning in Medical Imaging, by Keqiang Fan et al.
Non-negative Subspace Feature Representation for Few-shot Learning in Medical Imagingby Keqiang Fan, Xiaohao Cai, Mahesan…
Non-negative Subspace Feature Representation for Few-shot Learning in Medical Imagingby Keqiang Fan, Xiaohao Cai, Mahesan…
Self-Demos: Eliciting Out-of-Demonstration Generalizability in Large Language Modelsby Wei He, Shichun Liu, Jun Zhao, Yiwen…
HeGTa: Leveraging Heterogeneous Graph-enhanced Large Language Models for Few-shot Complex Table Understandingby Rihui Jin, Yu…
MFORT-QA: Multi-hop Few-shot Open Rich Table Question Answeringby Che Guan, Mengyu Huang, Peng ZhangFirst submitted…
Leveraging Large Language Models for Relevance Judgments in Legal Case Retrievalby Shengjie Ma, Chong Chen,…
Language Models for Text Classification: Is In-Context Learning Enough?by Aleksandra Edwards, Jose Camacho-ColladosFirst submitted to…
LLMs Are Few-Shot In-Context Low-Resource Language Learnersby Samuel Cahyawijaya, Holy Lovenia, Pascale FungFirst submitted to…
Towards Human-Like Machine Comprehension: Few-Shot Relational Learning in Visually-Rich Documentsby Hao Wang, Tang Li, Chenhui…
MedPromptX: Grounded Multimodal Prompting for Chest X-ray Diagnosisby Mai A. Shaaban, Adnan Khan, Mohammad YaqubFirst…
CoLLEGe: Concept Embedding Generation for Large Language Modelsby Ryan Teehan, Brenden Lake, Mengye RenFirst submitted…