Page 2: 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

To defend your software, first teach AI to break it

When Ying Zhang was a doctoral student at Virginia Tech, she spent years learning to think like an attacker—probing software for the hidden weaknesses that developers miss and malicious actors exploit.

Machine learning & AI

New AI research improves how computers interpret the world

For artificial intelligence tools that rely on interpreting data from the real world, both speed and accuracy are critically important. Researchers at the University of Saskatchewan (USask) have developed a tool to make AI ...

Machine learning & AI

Automation system advances efficient AI workflows

Your online order arrives damaged, so you request a refund. What often follows is an artificial intelligence workflow involving multiple AI models: One model checks your request against company policy, another analyzes the ...

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