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Eugene Yan launches AlignEval to simplify and automate LLM evaluation

Eugene Yan has launched AlignEval, a new application designed to simplify and automate the process of evaluating large language models (LLMs). The tool guides users through uploading data, labeling samples as pass or fail, defining evaluation criteria, and optimizing LLM-based evaluators. AlignEval emphasizes a data-first approach, encouraging users to derive evaluation criteria from actual model outputs rather than pre-defined metrics, aiming to reduce bottlenecks in AI product development. AI

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RANK_REASON Launch of a new application that simplifies a common task in AI development.

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COVERAGE [2]

  1. Eugene Yan TIER_1 ·

    AlignEval: Building an App to Make Evals Easy, Fun, and Automated

    Look at and label your data, build and evaluate your LLM-evaluator, and optimize it against your labels.

  2. Smol AINews TIER_1 ·

    Evals: The Next Generation

    **Scale AI** highlighted issues with data contamination in benchmarks like **MMLU** and **GSM8K**, proposing a new benchmark where **Mistral** overfits and **Phi-3** performs well. **Reka** released the **VibeEval** benchmark for multimodal models addressing multiple choice bench…