Research news on Large language models

Large language models are high-capacity neural sequence models trained on massive text and multimodal corpora to perform language understanding, generation, and reasoning. Current work examines their internal representations, cognitive and social behavior analogies to humans, and limitations in mathematical, causal, and strategic reasoning. Research also addresses alignment with human values and brain activity, safety and security vulnerabilities, privacy and de-anonymization risks, cross-lingual and sociocultural biases, scaling and efficiency laws, and frameworks for tool use, multi-agent interaction, and domain-specific deployment.

Machine learning & AI

New framework cuts costs, improves speed of summarization algorithms

Systems that can create summaries from conversations are in high demand in customer service, newsrooms and virtual assistants. Research published in the International Journal of Applied Pattern Recognition could improve processing ...

Automotive

AI analysis links pavement conditions to crash risk

A University of Houston professor of civil and environmental engineering is using artificial intelligence to make roads safer by connecting information that is usually analyzed separately. Lu Gao used AI to analyze large-scale ...

Computer Sciences

Researchers develop key technology to make personalized AI safer

The era of building "personalized AI" by training AI models on individual or corporate documents and data is beginning. However, while such customization can improve task performance, it can also weaken a model's existing ...

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