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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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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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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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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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Image Inpainting for SDXL 1.0 Base Model + Refiner
In this article, we’ll compare the results of SDXL 1.0 with its predecessor, Stable Diffusion 2.0. We’ll also take a…
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Explainable AI: Visualizing Attention in Transformers
In this article we explore one of the most popular tools for visualizing the core distinguishing feature of transformer architectures:…
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SAM + Stable Diffusion for Text-to-Image Inpainting
In this article, we’ll leverage the power of SAM, the first foundational model for computer vision, along with Stable Diffusion,…
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Debugging Image Classifiers With Confusion Matrices
Introduction We often rely on scalar metrics and static plots to describe and evaluate machine learning models, but these methods…
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Compare Object Detection Models From TorchVision
Introduction Object detection is one of the most popular applications of machine learning for computer vision. A detection model predicts…
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Author: Abby Morgan
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