Page 20: 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.

Consumer & Gadgets

Q&A: Can AI persuade you to go vegan—or harm yourself?

Large language models are more persuasive than humans, according to recent UBC research published as part of the Proceedings of the Third Workshop on Social Influence in Conversations (SICon 2025).

Machine learning & AI

Dialogue systems learn new words with fewer questions

Researchers at the University of Osaka have developed a mechanism that allows spoken dialog systems to learn new words through conversation without overwhelming users with repetitive questions. By optimizing when to ask a ...

Consumer & Gadgets

Apertus: A fully open, transparent, multilingual language model

In July, EPFL, ETH Zurich, and CSCS announced their joint initiative to build a large language model (LLM). Now, this model is available and serves as a building block for developers and organizations for future applications ...

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