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Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), UAE
CMU Machine Learning4
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8
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Detecting AI-generated code is harder than you think: even state-of-the-art detectors fail to reliably identify machine-written code, especially when faced with distribution shifts or adversarial attacks.
Training VLMs on a unified, multilingual, multitask meme dataset reveals that robust meme understanding requires multimodal training and is highly sensitive to dataset-specific overfitting.
A new open-source Hindi LLM, Nanda, outperforms existing models of similar scale by strategically balancing Hindi and English training data.
LLM360 K2 unveils the black box of large language model training, offering a 65B parameter model that beats LLaMA-65B while using fewer resources, all under a fully transparent, open-source framework.
