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Merging Strategies for Safer AI: A Dive into Self-Critique
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In the paper Merging Improves Self-Critique Against Jailbreak Attacks (PDF), the authors address how to make language models more resilient against adversarial jailbreak attempts like prompt manipulations intended to bypass a model’s safeguards. They present a method that merges the original model with a specialized critic model, enhancing its ability…
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Transforming Language Models: The Power of Dynamic Routing
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In From Fine-Tuning to Fusion: The Role of Agentic AI in Model Merging, the author explores how agentic AI systems can go beyond traditional fine-tuning by combining multiple specialized language models into a single, more capable whole. The article introduces the idea of model merging—not just blending models arbitrarily, but…
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Transforming News Analysis Using Compact Language Models
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In News Classification by Fine-tuning Small Language Models, the author explains how Small Language Models (SLMs)—typically models under 10 billion parameters—offer an efficient, cost-effective alternative to larger models, particularly in resource-constrained settings. The article emphasizes how fine-tuning these compact models using techniques like parameter-efficient methods (e.g., LoRA) enables high performance…
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