Researchers at the National Institute of Informatics (NII) co-authored 20 papers accepted at ACL 2026, the world's foremost conference in natural language processing. Remarkably, two of these papers earned major honors: one received the Best Theme Paper award and another the Outstanding Paper award. A third paper was further selected for a Best Paper Award, the conference's highest distinction, underscoring NII's growing presence and impact at the leading international venue for the field.

A new honeybee-inspired analysis suggests that central control isn’t necessary for group success, as long as there’s good communication and just the right mix of risk-takers and cautious followers.

In 2024, scientists demonstrated quantum teleportation in a lab-based cable filled with high-speed internet traffic. New study sent entangled photons through a busy cable connecting Evanston to downtown Chicago. Quantum signals remained remarkably intact, preserving entanglement with more than 94% fidelity. Work demonstrates practical path to building quantum networks without needing new communications infrastructure.

USC is among the first universities selected to help lead the U.S. Department of Energy’s Genesis Mission, a national initiative that unites the country’s 17 national laboratories, universities and industry to explore artificial intelligence for scientific discovery.

The study tests a chaos-based encryption scheme on real patient scans and report categories, aiming to keep e-healthcare data safe as it disseminates across the internet. Hospitals and clinics increasingly store and share patient information digitally in the form of X-rays, CT scans, and other medical images that deeply reveal personal health details. This convenience comes with risk: once this data moves across the internet, it becomes a target for interception or tampering. A new study, published ahead of print in Wireless and Communication Letters, proposes a way to protect these images using the mathematics of chaos.

Unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) was used for high throughput maize plant height phenotyping in 270 doubled haploid (DH) lines across multiple stages and environments. Single plant scale estimation outperformed row scale, with R² values of 0.67 vs. 0.56 and RMSE values of 0.12 m vs. 0.17 m, respectively. Using inclusive composite interval mapping, we identified 12 and 20 QTLs for plant height in two DH populations. These results support the feasibility of UAV-based QTL mapping and candidate gene discovery in maize.