Page 11: 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

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 ...

Machine learning & AI

Toward a new framework to accelerate large language model inference

High-quality output at low latency is a critical requirement when using large language models (LLMs), especially in real-world scenarios, such as chatbots interacting with customers, or the AI code assistants used by millions ...

Computer Sciences

LLMs can match human brain perceptions in everyday scenes

When we look at the world, our brain doesn't just recognize objects such as "a dog" or "a car," it also understands the broader meaning, like what's happening, where it's happening, and how everything fits together. But for ...

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