WHEN A LARGE language model (LLM) gives a cardiologist a poor answer, it is not always the model that is the only problem. More often ...

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.

When I quit, I realized the app had become progressively worse the whole time I was forcing myself through it. I'm not alone.

A new study suggests that learning and remembering speech relies more on how the brain processes sounds and sensations than on the areas that control mouth and face movements. The discovery could ...

By feeding centuries-old nursery rhymes and folklore recordings into their own model, linguists in Louisiana hope to help a ...

Abstract: This paper investigates adaptive transmission strategies in embodied AI-enhanced vehicular networks by integrating vision language models (VLMs) for semantic information extraction and deep ...

Spelling methods that teach nonspeakers to point to letters to spell words are controversial because they require a ...

Abstract: Deep reinforcement learning (DRL) has been widely applied to tackle energy management tasks and provide real-time decision support. However, existing studies face inherent limitations of DRL ...

Researchers have created a protein that can detect the faint chemical signals neurons receive from other brain cells. By tracking glutamate in real time, scientists can finally see how neurons process ...

When enterprises fine-tune LLMs for new tasks, they risk breaking everything the models already know. This forces companies to maintain separate models for every skill. Researchers at MIT, the ...

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