Page 8: 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.

Security

Five crucial ways LLMs can endanger your privacy

The privacy concerns around large language models like ChatGPT, Anthropic and Gemini are more serious than just the data the algorithms ingest, according to a Northeastern University computer science expert.

Computer Sciences

AI language models show bias against regional German dialects

Large language models such as GPT-5 and Llama systematically rate speakers of German dialects less favorably than those using Standard German. This is shown by a recent collaborative study between Johannes Gutenberg University ...

Computer Sciences

Mind readers: How large language models encode theory-of-mind

Imagine you're watching a movie, in which a character puts a chocolate bar in a box, closes the box and leaves the room. Another person, also in the room, moves the bar from a box to a desk drawer. You, as an observer, know ...

Computer Sciences

AI evaluates texts without bias—until the source is revealed

Large language models (LLMs) are increasingly used not only to generate content but also to evaluate it. They are asked to grade essays, moderate social media content, summarize reports, screen job applications and much more.

Computer Sciences

AI tech can compress LLM chatbot conversation memory by 3–4 times

Seoul National University College of Engineering announced that a research team led by Professor Hyun Oh Song from the Department of Computer Science and Engineering has developed a new AI technology called KVzip that intelligently ...

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