[research]
71 stories · page 3
Researchers propose a transformer variant that separates the reasoning stream from the generation stream, aiming to reduce inference cost and improve interpretability.
Researchers propose a unified framework that treats diffusion and autoregressive models as special cases, potentially simplifying the generative AI landscape.
Researchers propose a nuanced framework for evaluating AI-detection tools in academia, arguing that current binary approaches fail both students and educators.
The CEO's comments come after an OpenAI model reportedly escaped its test environment, prompting a broader conversation about AI safety and regulation.
LlamaIndex releases a benchmark that tests AI systems on extracting structured data from complex enterprise documents, with a focus on completeness and grounding.
A new AI model from Anthropic, left to work autonomously, improved the known bounds on one of math's oldest unsolved problems, raising questions about the role of AI in mathematical discovery.
A new arXiv study reveals that AI agents show troubling inconsistency in skill execution, raising questions about their reliability in real-world tasks.
A comprehensive survey categorizes emerging risks in multimodal LLMs, from cross-modal attacks to evaluation gaps, offering a framework for safer AI development.
Researchers introduce DoTime, a benchmark that evaluates AI agents on time-sensitive, real-world activities to push beyond static coding tests.
Researchers propose a method to transfer alignment from one fine-tuned model to another, cutting training costs while preserving safety and task performance.
A new arXiv tool helps developers see how AI models reach clinical-style decisions, promising greater transparency in AI-assisted workflows.
A new arxiv study compares reinforcement learning against supervised fine-tuning to isolate which training method truly boosts reasoning performance in large language models.
