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LLM Evaluation Complexities for Non-Latin Languages
Large language models (LLMs) have revolutionized natural language processing, yet most development and evaluation efforts have historically centered around Latin-script…
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SelfCheckGPT for LLM Evaluation
Detecting hallucinations in language models is challenging. There are three general approaches: The problem with many LLM-as-a-Judge techniques is that…
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LLM Juries for Evaluation
Evaluating the correctness of generated responses is an inherently challenging task. LLM-as-a-Judge evaluators have gained popularity for their ability to…
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LLM Monitoring & Maintenance in Production Applications
Generative AI has become a transformative force, revolutionizing how businesses engage with users through chatbots, content creation, and personalized recommendations.…
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G-Eval for LLM Evaluation
LLM-as-a-judge evaluators have gained widespread adoption due to their flexibility, scalability, and close alignment with human judgment. They excel at…
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BERTScore For LLM Evaluation
Introduction BERTScore represents a pivotal shift in LLM evaluation, moving beyond traditional heuristic-based metrics like BLEU and ROUGE to a…
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Building ClaireBot, an AI Personal Stylist Chatbot
Follow the evolution of my personal AI project and discover how to integrate image analysis, LLM models, and LLM-as-a-judge evaluation…
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Perplexity for LLM Evaluation
Perplexity is, historically speaking, one of the “standard” evaluation metrics for language models. And while recent years have seen a…
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Meet Opik: Your New Tool to Evaluate, Test, and Monitor LLM Applications
Today, we’re thrilled to introduce Opik – an open-source, end-to-end LLM development platform that provides the observability tools you need…
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Building a Low-Cost Local LLM Server to Run 70 Billion Parameter Models
A guest post from Fabrício Ceolin, DevOps Engineer at Comet. Inspired by the growing demand for large-scale language models, Fabrício…
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