Large language models (LLMs) have achieved significant performance progress in various natural language processing applications. However, LLMs still struggle to meet the strict requirements for accuracy and reliability in the medical field and face many challenges in clinical applications. Existing clinical diagnostic evaluation benchmarks for evaluating medical agents powered by LLMs have severe limitations. Firstly, most existing medical evaluation benchmarks face the risk of data leakage or contamination.

Neural Information Processing Systems http://nips.cc/

Despite today's drop in software and data companies, the UK's FTSE 100 share index is down just 0.07% this session as investors rotate into other sectors. Worryingly, that pattern "echoes what we saw in 2000 as the dot-com bubble started to burst", analysts at Deutsche

The lesser long-nosed bat (Leptonycteris yerbabuenae) is a medium-sized bat found in Central and North America. Breakthroughs, discoveries, and DIY tips sent six days a week. Biologists and engineers have joined forces to build a new robot bat that's helping us understand how bats use echolocation to hunt for food. By creating a robot that can echolocate, the team mimicked a bat's flight path and explained how bats can quickly determine whether or not their prey is on a leaf. This new bat's eye view is detailed in a study recently published in the The study was led in part by bat scientist and Smithsonian Tropical Research Institute research associate Inga Geipel .

Radar is ubiquitous in autonomous driving systems due to its low cost and good adaptability to bad weather. Nevertheless, the radar detection performance is usually inferior because its point cloud is sparse and not accurate due to the poor azimuth and elevation resolution. Moreover, point cloud generation algorithms already drop weak signals to reduce the false targets which may be suboptimal for the use of deep fusion. In this paper, we propose a novel method named EchoFusion to skip the existing radar signal processing pipeline and then incorporate the radar raw data with other sensors. Specifically, we first generate the Bird's Eye View (BEV) queries and then take corresponding spectrum features from radar to fuse with other sensors. By this approach, our method could utilize both rich and lossless distance and speed clues from radar echoes and rich semantic clues from images, making our method surpass all existing methods on the RADIal dataset, and approach the performance of LiDAR.

Neural Information Processing Systems http://nips.cc/

Neural Information Processing Systems http://nips.cc/

The rapid rise of Generative AI (GenAI), particularly LLMs, poses concerns for journalistic integrity and authorship. This study examines AI-generated content across over 40,000 news articles from major, local, and college news media, in various media formats. Using three advanced AI-text detectors (e.g., Binoculars, Fast-Detect GPT, and GPTZero), we find substantial increase of GenAI use in recent years, especially in local and college news. Sentence-level analysis reveals LLMs are often used in the introduction of news, while conclusions usually written manually. Linguistic analysis shows GenAI boosts word richness and readability but lowers formality, leading to more uniform writing styles, particularly in local media.