AI Benchmarking

294 summarised stories about AI Benchmarking, each linking back to the original source. Browse all topics →

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Monday, 24 August 2026

Fastino Releases GLiNER2.5: A Boundary-Prediction Architecture That Removes Span Enumeration From Information Extraction

MarkTechPost 1 month ago 34

Fastino released GLiNER2.5, which replaces span enumeration with a boundary-prediction architecture for information extraction. It supports 4,096-word context windows and reports 56.17 overall macro F1 on 16 multilingual zero-shot benchmarks. The shift enables longer entities, removes the width ceiling, and adds joint entity-relation decoding with constrained labels and span attributes, while releasing 74M/194M/287M-parameter checkpoints on Hugging Face for self-hosted CPU/CUDA/MPS inference.

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AI Benchmarking Model Releases Open Source Models Multimodal AI

Kids outlearn AI—and we still don’t know why

MIT Technology Review 1 month ago 36

Researchers say today’s large language models need far more training data than human children to learn language, creating a “data efficiency gap” that remains unexplained. BabyLM—the benchmark competition meant to test child-scale learning—asks teams to train models on a developmentally plausible corpus of 100 million words (10 million for the toddler track). The field is shifting toward evaluating and designing more data-efficient AI systems that better match how children acquire grammar, instead of relying only on scaling up data.

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AI Benchmarking Language Models AI Efficiency AI & Academia

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