Latest Articles for Zero-shot Learning

New method improves image classification with minimal data using unlabeled images.

A new approach allows machines to identify comic characters without prior training.

A new method creates dialogue systems using unlabelled data and APIs.

This article examines how social media influences political opinions during elections.

This method enhances language model fine-tuning using open, unlabeled datasets.

LangCell combines cell data and natural language for better cell analysis.

I2CL improves efficiency and performance in language model tasks.

TAGA offers a new way to analyze Text-Attributed Graphs without extensive labeled data.

TransCLIP enhances predictions by integrating visual and textual data in Vision-Language Models.

A study on how context affects leaderboard generation in AI research.

Exploring methods for effective multi-label classification in software development.

RetiZero enhances eye disease identification using advanced AI techniques and extensive data.

New methods enhance robots' ability to detect environmental changes without training.

This paper explores ensemble methods for effective few-shot learning with language models.

Robots can now follow natural language commands more effectively.

New learning methods are reshaping AI applications in the medical field.

New method enhances learning in image-text models using composite examples.

CodeCSE improves linking code and comments using contrastive learning for software engineering.

New techniques allow for better emulation of guitar amplifiers and effects.

Introducing STD-LLM for improved forecasting and imputation in dynamic systems.

A look at how open-source models measure up against commercial counterparts in biomedical tasks.

New methods enhance action recognition in visual data with skeleton analysis.

New techniques enhance communication underwater using gesture recognition.

GET-Zero enhances robots' adaptability across varied designs without extensive retraining.

A new approach enhances zero-shot learning for better IoT data classification.

ETHOS uses AI to predict patient health changes effectively.

Research on using Graph Neural Networks for efficient power grid state estimation.

Assessing how well LLMs produce JSON outputs through StructuredRAG tests.

A novel approach improves species distribution predictions using advanced AI techniques.

HOIGen introduces a new method for recognizing unseen human-object interactions.

Examining the role of foundation models in overcoming data scarcity in medical imaging.

Humanoid robots learn to navigate tough terrains through a new approach.

This article explores the role of memorization in improving ICL performance.

Exploring how LLMs are shaping the future of healthcare.

PromptSmooth improves Med-VLMs' accuracy against adversarial attacks efficiently.

RevCD enhances zero-shot learning by linking visual and semantic information for unseen categories.

Open-source models that efficiently classify political texts without extensive training.

This article examines how relative representations improve AI communication and task adaptability.

Evaluating VLMs on spatial tasks using visual and unclear text.

This study evaluates zero-shot and few-shot learning in clinical applications.