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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: Measuring token-level probability distributions for indications that a…
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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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Intro to LLM Observability: What to Monitor & How to Get Started
While LLM usage is soaring, productionizing an LLM-powered application or software product presents new and different challenges compared to traditional…
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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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