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Chris

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reacted to codelion's post with šŸ¤— 5 days ago
Adaptive Classifier: Dynamic Text Classification with Strategic Learning New text classification system that learns continuously without catastrophic forgetting. Achieved 22.2% robustness improvement on adversarial datasets while maintaining clean data performance. šŸŽÆ THE PROBLEM Traditional classifiers require complete retraining when adding new classes. Expensive and time-consuming, especially with adversarial users trying to game the system. šŸš€ KEY INNOVATIONS ā€¢ Hybrid memory-neural architecture (prototype-based + neural adaptation) ā€¢ Strategic classification using game theory to predict and defend against manipulation ā€¢ Elastic Weight Consolidation prevents catastrophic forgetting šŸ“Š RESULTS Tested on AI-Secure/adv_glue dataset: ā€¢ Clean data: 80.0% ā†’ 82.2% (+2.2%) ā€¢ Manipulated data: 60.0% ā†’ 82.2% (+22.2%) ā€¢ Zero performance drop under adversarial attacks šŸ”¬ APPLICATIONS ā€¢ Hallucination detection: 80.7% recall for RAG safety ā€¢ LLM routing: 26.6% cost optimization improvement ā€¢ Content moderation: Robust against gaming attempts āš™ļø USAGE pip install adaptive-classifier from adaptive_classifier import AdaptiveClassifier classifier = AdaptiveClassifier("bert-base-uncased") classifier.add_examples(texts, labels) predictions = classifier.predict("New text") šŸ”— RESOURCES Blog: https://huggingface.co/blog/codelion/adaptive-classifier Code: https://github.com/codelion/adaptive-classifier Models: https://huggingface.co/adaptive-classifier Available models: llm-hallucination-detector, llm-config-optimizer, llm-router Works with any HuggingFace transformer. Fully open source and production-ready!
new activity 2 months ago
mradermacher/model_requests:Model request GLM-4-0414 series model
updated a model 2 months ago
WesPro/Broken-Tutu-24B-Q6_K-GGUF
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