Simplifying the latest STEM breakthroughs for all.
Highlights: New fusion-based method can generate high-specific-activity radioisotopes essential for medicine. Utilizes high-energy neutrons from deuterium-tritium (D-T) fusion to drive transmutation reactions. Offers a non-fission, proliferation-resistant alternative to reactor-based isotope…
Highlights: PLUTO-4 introduces frontier-scale foundation models for digital pathology. Features two architectures: PLUTO-4S for efficiency and PLUTO-4G for maximal precision. Trained on over 551,000 whole-slide images (WSIs) from more than…
Highlights: Researchers develop a new randomized search model integrating social learning with area-restricted search (ARS). Findings reveal a trade-off between group efficiency, temporal stability, and equity in resource distribution. Optimal…
Highlights: Introduces ‘Modules of Influence’ (MoI) for analyzing model explanation graphs. Uses community detection algorithms to identify groups of interacting features. Improves model interpretability, debugging, and bias localization. Offers open-source…
Highlights: Researchers introduce ‘Modules of Influence’ (MoI), a framework combining graph analysis with model explainability. MoI constructs model explanation graphs and applies community detection to expose interacting feature modules. The…
Highlights: Researchers demonstrate how personalized AI scaffolds enhance creative collaboration. Study shows fully personalized LLM assistants significantly boost creativity and task quality. Personalization strengthens user trust, confidence, and cognitive synergy.…
Highlights: Researchers introduce new methods to improve large language models (LLMs) for code vulnerability detection. Study explores two selection criteria for choosing few-shot examples in in-context learning (ICL). Approach combines…
Highlights: Researchers demonstrate that personalization significantly enhances human-AI synergy in creative tasks. Personalized AI systems leverage psychometric profiles and user style interviews to co-create marketing content. Study involving 331 participants…
Highlights: Perplexity AI introduces TransferEngine, a portable RDMA communication layer for LLM systems. Achieves peak throughput of 400 Gbps on NVIDIA ConnectX-7 and AWS Elastic Fabric Adapter (EFA). Enables flexible…
Highlights: Introduces Masked Diffusion Captioning (MDC) for visual feature learning. Developed by Chao Feng, Zihao Wei, and Andrew Owens. Uses an image-conditioned masked diffusion language model to train visual representations.…