Discover how Mixture-of-Adaptations uses random routing and weight merging to fine-tune language models with less cost and better performance. #fewshotlearning
How Mixture-of-Adaptations Makes Language Model Fine-Tuning Cheaper and Smarter
hackernoon.com
October 1, 2025 at 9:00 AM
Discover how Mixture-of-Adaptations uses random routing and weight merging to fine-tune language models with less cost and better performance. #fewshotlearning
AdaMix improves fine-tuning of large language models by mixing adaptation modules—outperforming full tuning with just 0.2% parameters. #fewshotlearning
Beating Full Fine-Tuning with Just 0.2% of Parameters
hackernoon.com
October 2, 2025 at 7:00 AM
AdaMix improves fine-tuning of large language models by mixing adaptation modules—outperforming full tuning with just 0.2% parameters. #fewshotlearning
CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification
New methodology CBVLM combines LVLMs and concept-based explanations to improve medical workflow adoption. #interpretability #fewshotlearning
Read more: https://arxiv.org/html/2501.12266v1
New methodology CBVLM combines LVLMs and concept-based explanations to improve medical workflow adoption. #interpretability #fewshotlearning
Read more: https://arxiv.org/html/2501.12266v1
January 24, 2025 at 11:42 AM
CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification
New methodology CBVLM combines LVLMs and concept-based explanations to improve medical workflow adoption. #interpretability #fewshotlearning
Read more: https://arxiv.org/html/2501.12266v1
New methodology CBVLM combines LVLMs and concept-based explanations to improve medical workflow adoption. #interpretability #fewshotlearning
Read more: https://arxiv.org/html/2501.12266v1
Fun fact: Few-shot learning lets ChatGPT adapt with minimal examples!
• Parameter scaling matters.
• Real-world uses expand.
• Ethical considerations in focus.
👉 superwebtools.in/the-history-and-power-of-chatgpt
#FewShotLearning #EthicalAI #ChatGPT #USA #UnitedStates #Wednesday #AI #Technology
• Parameter scaling matters.
• Real-world uses expand.
• Ethical considerations in focus.
👉 superwebtools.in/the-history-and-power-of-chatgpt
#FewShotLearning #EthicalAI #ChatGPT #USA #UnitedStates #Wednesday #AI #Technology
Innovative Breakthroughs: The History and Power of ChatGPT 2025💡 - SuperWebTools
The History and Power of ChatGPT unveils its evolution from GPT‑1’s inception to GPT‑4o’s multi‑modal breakthroughs, highlighting transformative AI milestones, industry‑shaping innovations, and real‑w...
superwebtools.in
May 14, 2025 at 4:12 PM
Fun fact: Few-shot learning lets ChatGPT adapt with minimal examples!
• Parameter scaling matters.
• Real-world uses expand.
• Ethical considerations in focus.
👉 superwebtools.in/the-history-and-power-of-chatgpt
#FewShotLearning #EthicalAI #ChatGPT #USA #UnitedStates #Wednesday #AI #Technology
• Parameter scaling matters.
• Real-world uses expand.
• Ethical considerations in focus.
👉 superwebtools.in/the-history-and-power-of-chatgpt
#FewShotLearning #EthicalAI #ChatGPT #USA #UnitedStates #Wednesday #AI #Technology
Key insights into the evolution, trends, and gaps in few-shot learning across hyperspectral, SAR, and VHR remote sensing domains. #fewshotlearning
Few-Shot Learning in Remote Sensing: Trends, Gaps, and Future Directions
hackernoon.com
June 11, 2025 at 2:58 PM
Key insights into the evolution, trends, and gaps in few-shot learning across hyperspectral, SAR, and VHR remote sensing domains. #fewshotlearning
Discover the 3 main types of remote sensing sensor data—VHR, hyperspectral, and SAR—and how they impact machine learning and Earth observation. #fewshotlearning
Understanding the 3 Main Types of Remote Sensing Sensor Data
hackernoon.com
June 10, 2025 at 3:12 AM
Discover the 3 main types of remote sensing sensor data—VHR, hyperspectral, and SAR—and how they impact machine learning and Earth observation. #fewshotlearning
Explore 6 recent few-shot learning techniques revolutionizing hyperspectral image classification in satellite and UAV-based remote sensing. #fewshotlearning
6 Breakthrough Few-Shot Learning Techniques for Remote Sensing
hackernoon.com
June 11, 2025 at 2:39 PM
Explore 6 recent few-shot learning techniques revolutionizing hyperspectral image classification in satellite and UAV-based remote sensing. #fewshotlearning
Explore how few-shot learning enables object detection and segmentation in remote sensing using minimal training data with improved explainability. #fewshotlearning
Smarter Satellite Vision with Few-Shot Learning
hackernoon.com
June 11, 2025 at 2:23 PM
Explore how few-shot learning enables object detection and segmentation in remote sensing using minimal training data with improved explainability. #fewshotlearning
Learn the top 5 metrics to evaluate few-shot remote sensing models, from confusion matrix to F1 score, and how they handle data imbalance. #fewshotlearning
5 Key Metrics to Evaluate Few-Shot Remote Sensing Models
hackernoon.com
June 10, 2025 at 3:13 AM
Learn the top 5 metrics to evaluate few-shot remote sensing models, from confusion matrix to F1 score, and how they handle data imbalance. #fewshotlearning
Few-shot learning and XAI are transforming remote sensing with smarter, faster, and more transparent AI systems that work with limited data. #fewshotlearning
The Future of Remote Sensing: Few-Shot Learning and Explainable AI
hackernoon.com
June 12, 2025 at 10:00 AM
Few-shot learning and XAI are transforming remote sensing with smarter, faster, and more transparent AI systems that work with limited data. #fewshotlearning
AdaMix outperforms fine-tuning and top PEFT methods across NLU, NLG, and few-shot NLP tasks, proving both efficient and powerful. #fewshotlearning
Smarter Fine-Tuning for NLU and NLG Tasks
hackernoon.com
October 1, 2025 at 11:00 AM
AdaMix outperforms fine-tuning and top PEFT methods across NLU, NLG, and few-shot NLP tasks, proving both efficient and powerful. #fewshotlearning
Explore benchmark datasets for remote sensing, including hyperspectral, VHR, UAV, and SAR imagery—perfect for evaluating ML models. #fewshotlearning
Top Remote Sensing Datasets for Training and Evaluating AI Models
hackernoon.com
June 10, 2025 at 3:13 AM
Explore benchmark datasets for remote sensing, including hyperspectral, VHR, UAV, and SAR imagery—perfect for evaluating ML models. #fewshotlearning
Benchmarking 9 few-shot learning methods on UAV disaster imagery using AIDER and UC-Merced datasets—Label Hallucination tops with over 81% accuracy.
#fewshotlearning
#fewshotlearning
Few-Shot Deep Learning Shows Promise for Remote Sensing Applications
hackernoon.com
June 12, 2025 at 8:00 AM
Benchmarking 9 few-shot learning methods on UAV disaster imagery using AIDER and UC-Merced datasets—Label Hallucination tops with over 81% accuracy.
#fewshotlearning
#fewshotlearning
🌟 Master Few-Shot Learning! 🌟
Quick guide on few-shot learning—a method for training models w/ minimal data! 🧠✨
Learn:
- Prototypical/Matching Networks
- Overfitting fixes & data augmentation 📊
👀 Watch the 🔗 full video 👉: https://link.illustris.org/aiminimaldata
#AI #FewShotLearning
Quick guide on few-shot learning—a method for training models w/ minimal data! 🧠✨
Learn:
- Prototypical/Matching Networks
- Overfitting fixes & data augmentation 📊
👀 Watch the 🔗 full video 👉: https://link.illustris.org/aiminimaldata
#AI #FewShotLearning
Discover How AI Learns with Minimal Data
🔍 Few-shot & Zero-shot Learning: How AI Thinks Like Us!
Large Language Models (LLMs) like ChatGPT can understand and generate text, but how do they handle brand-new tasks? Enter Few-shot and Zero-shot Learning!
🚀 What You'll Learn:
✅ What Few-shot and Zero-shot Learning are
✅ How AI learns with minimal examples
✅ Real-world applications in translation, coding, and automation
✅ Example Python code demonstrating AI's power
💡 These techniques make AI smarter, faster, and more adaptable-shaping the future of automation and creativity!
🔗 Watch now to stay ahead in AI innovation!
#AI #MachineLearning #FewShotLearning #ZeroShotLearning #ArtificialIntelligence #TechExplained #DeepLearning
▬▬▬▬▬▬ 🔗 Additional Info 🔗 ▬▬▬▬▬▬
✍️ Blog: https://dougortiz.blogspot.com/
▬▬▬▬▬▬ 👋 Contact me 👋 ▬▬▬▬▬▬
➡ LinkedIn: https://www.linkedin.com/in/doug-ortiz-illustris/
▬▬▬▬▬▬ ⏱ Timestamps ⏱ ▬▬▬▬▬▬
00:00 Introduction
00:20 Concepts
01:01 Use Case Scenarios
01:32 Who Benefits?
01:49 Why Do They Matter?
02:10 Related Technologies and Integration
02:29 Conclusion
link.illustris.org
February 15, 2025 at 12:08 AM
🌟 Master Few-Shot Learning! 🌟
Quick guide on few-shot learning—a method for training models w/ minimal data! 🧠✨
Learn:
- Prototypical/Matching Networks
- Overfitting fixes & data augmentation 📊
👀 Watch the 🔗 full video 👉: https://link.illustris.org/aiminimaldata
#AI #FewShotLearning
Quick guide on few-shot learning—a method for training models w/ minimal data! 🧠✨
Learn:
- Prototypical/Matching Networks
- Overfitting fixes & data augmentation 📊
👀 Watch the 🔗 full video 👉: https://link.illustris.org/aiminimaldata
#AI #FewShotLearning
Ablation studies on AdaMix reveal why adaptation merging, consistency regularization, and module sharing drive superior fine-tuning performance. #fewshotlearning
The Role of Consistency and Sharing in Efficient Fine-Tuning
hackernoon.com
October 1, 2025 at 1:00 PM
Ablation studies on AdaMix reveal why adaptation merging, consistency regularization, and module sharing drive superior fine-tuning performance. #fewshotlearning
New!
We propose a novel memory-based extension for few-shot fault diagnosis — improving prototype estimation, generalization, and calibration in low-data industrial settings.
link.springer.com/article/10.1...
#MachineLearning #FaultDiagnosis #FewShotLearning #Industry40 #PredictiveMaintenance
We propose a novel memory-based extension for few-shot fault diagnosis — improving prototype estimation, generalization, and calibration in low-data industrial settings.
link.springer.com/article/10.1...
#MachineLearning #FaultDiagnosis #FewShotLearning #Industry40 #PredictiveMaintenance
Client Challenge
link.springer.com
October 14, 2025 at 8:35 AM
New!
We propose a novel memory-based extension for few-shot fault diagnosis — improving prototype estimation, generalization, and calibration in low-data industrial settings.
link.springer.com/article/10.1...
#MachineLearning #FaultDiagnosis #FewShotLearning #Industry40 #PredictiveMaintenance
We propose a novel memory-based extension for few-shot fault diagnosis — improving prototype estimation, generalization, and calibration in low-data industrial settings.
link.springer.com/article/10.1...
#MachineLearning #FaultDiagnosis #FewShotLearning #Industry40 #PredictiveMaintenance
A new task-level contrastive method boosts few-shot learning accuracy on the MetaDataset benchmark without adding parameters or extra computation. Read more: https://getnews.me/task-level-contrastiveness-boosts-cross-domain-few-shot-learning/ #fewshotlearning #contrastivelearning #metadataset
October 7, 2025 at 3:43 PM
A new task-level contrastive method boosts few-shot learning accuracy on the MetaDataset benchmark without adding parameters or extra computation. Read more: https://getnews.me/task-level-contrastiveness-boosts-cross-domain-few-shot-learning/ #fewshotlearning #contrastivelearning #metadataset
AdaMix fine-tunes large language models with just 0.1% of parameters, beating full fine-tuning in performance and efficiency. #fewshotlearning
How to Improve AI Models While Training Only 0.1% of Parameters
hackernoon.com
October 1, 2025 at 7:00 AM
AdaMix fine-tunes large language models with just 0.1% of parameters, beating full fine-tuning in performance and efficiency. #fewshotlearning
On Selecting Few-Shot Examples for LLM-based Code Vulnerability
Detection
Chi Zhang, Corina S. Pasareanu et al.
Paper
Details
#FewShotLearning #CodeVulnerabilityDetection #LLMResearch
Detection
Chi Zhang, Corina S. Pasareanu et al.
Paper
Details
#FewShotLearning #CodeVulnerabilityDetection #LLMResearch
November 5, 2025 at 5:02 PM
On Selecting Few-Shot Examples for LLM-based Code Vulnerability
Detection
Chi Zhang, Corina S. Pasareanu et al.
Paper
Details
#FewShotLearning #CodeVulnerabilityDetection #LLMResearch
Detection
Chi Zhang, Corina S. Pasareanu et al.
Paper
Details
#FewShotLearning #CodeVulnerabilityDetection #LLMResearch
Reviewing how few-shot learning enables UAV and satellite image classification with limited data, while enhancing model transparency using XAI.
#fewshotlearning
#fewshotlearning
How Few-Shot Learning Enhances UAV-Based Image Analysis
hackernoon.com
June 10, 2025 at 3:12 AM
Reviewing how few-shot learning enables UAV and satellite image classification with limited data, while enhancing model transparency using XAI.
#fewshotlearning
#fewshotlearning
Partial adaptation—weakening instruction‑tuning—boosts few‑shot learning on tasks like text classification and sentiment analysis. Presented at EMNLP 2025. Read more: https://getnews.me/partial-adaptation-boosts-few-shot-learning-in-instruct-models/ #partialadaptation #fewshotlearning
September 25, 2025 at 7:04 PM
Partial adaptation—weakening instruction‑tuning—boosts few‑shot learning on tasks like text classification and sentiment analysis. Presented at EMNLP 2025. Read more: https://getnews.me/partial-adaptation-boosts-few-shot-learning-in-instruct-models/ #partialadaptation #fewshotlearning
AdaMix proves its edge in few-shot NLU, consistently outperforming full fine-tuning across GLUE benchmarks with BERT and RoBERTa. #fewshotlearning
Smarter AI Training with Few-Shot Natural Language Tasks
hackernoon.com
October 2, 2025 at 9:00 AM
AdaMix proves its edge in few-shot NLU, consistently outperforming full fine-tuning across GLUE benchmarks with BERT and RoBERTa. #fewshotlearning
Concepts for working with little specific data to a given task have first gained significant relevance for AI with the first #GPT models. Their relevance has ever grown since. Thanks to architectures like #TabPFN it is also possible, to apply #FewShotLearning to applications, where precision is key.
February 20, 2025 at 10:50 PM
Concepts for working with little specific data to a given task have first gained significant relevance for AI with the first #GPT models. Their relevance has ever grown since. Thanks to architectures like #TabPFN it is also possible, to apply #FewShotLearning to applications, where precision is key.
🚀 New paper in Journal of Intelligent Manufacturing!
REMB: Regularized Embedding Memory Book improves few-shot fault diagnosis, reduces overfitting, and enhances model calibration under noise.
🔗 link.springer.com/article/10.1...
#AI #PredictiveMaintenance #FewShotLearning #SmartManufacturing
REMB: Regularized Embedding Memory Book improves few-shot fault diagnosis, reduces overfitting, and enhances model calibration under noise.
🔗 link.springer.com/article/10.1...
#AI #PredictiveMaintenance #FewShotLearning #SmartManufacturing
Remb: regularized embedding memory book to extend metric learning in fault diagnosis - Journal of Intelligent Manufacturing
Few-Shot Learning (FSL) has gained significant attention in fault diagnosis due to its ability to classify faults with limited labeled data. Metric learning-based approaches, such as prototypical netw...
link.springer.com
November 9, 2025 at 9:14 PM
🚀 New paper in Journal of Intelligent Manufacturing!
REMB: Regularized Embedding Memory Book improves few-shot fault diagnosis, reduces overfitting, and enhances model calibration under noise.
🔗 link.springer.com/article/10.1...
#AI #PredictiveMaintenance #FewShotLearning #SmartManufacturing
REMB: Regularized Embedding Memory Book improves few-shot fault diagnosis, reduces overfitting, and enhances model calibration under noise.
🔗 link.springer.com/article/10.1...
#AI #PredictiveMaintenance #FewShotLearning #SmartManufacturing
Learn how few-shot learning enables AI to make accurate predictions with minimal data, using techniques like contrastive loss and prototypical networks.
#fewshotlearning
#fewshotlearning
Few-Shot vs. One-Shot vs. Zero-Shot Learning
hackernoon.com
June 10, 2025 at 3:12 AM
Learn how few-shot learning enables AI to make accurate predictions with minimal data, using techniques like contrastive loss and prototypical networks.
#fewshotlearning
#fewshotlearning