Latest AI and machine learning research in medicare for healthcare professionals.
We introduce COU: Common Objects Underwater, an instance-segmented image dataset of commonly found man-made objects in multiple aquatic and marine environments. COU contains approximately 10K segmented images, annotated from images collected during a number of underwater robot field trials in diverse locations. COU has been created to address the lack of datasets with robust class coverage curat...
Long-context Multimodal Large Language Models (MLLMs) that incorporate long text-image and text-video modalities, demand substantial resources as their multimodal Key-Value (KV) caches grow with increasing input lengths, challenging inference efficiency. Existing methods for KV cache compression, in both text-only and multimodal LLMs, have neglected attention density variations across layers, th...
Novel research aimed at text-to-image (T2I) generative AI safety often relies on publicly available datasets for training and evaluation, making the...
Medicare fraud poses a substantial challenge to healthcare systems, resulting in significant financial losses and undermining the quality of care pr...
Testing processes usually aim at high coverage, but loops severely limit coverage ambitions since the number of iterations is generally not predicta...
Existing Large Vision-Language Models (LVLMs) can process inputs with context lengths up to 128k visual and text tokens, yet they struggle to genera...
Purpose: Comprehensive legal medicine documentation includes both an internal but also an external examination of the corpse. Typically, this docume...
Accurately locating key moments within long videos is crucial for solving long video understanding (LVU) tasks. However, existing benchmarks are eit...
Single-cell proteomics (SCP) is transforming our understanding of biological complexity by shifting from bulk proteomics, where signals are averaged...
The efficient processing of long context poses a serious challenge for large language models (LLMs). Recently, retrieval-augmented generation (RAG) ...
Identifying cognitive impairment within electronic health records (EHRs) is crucial not only for timely diagnoses but also for facilitating research...
Catheter ablation of Atrial Fibrillation (AF) consists of a one-size-fits-all treatment with limited success in persistent AF. This may be due to ou...
The sharing of large-scale transportation data is beneficial for transportation planning and policymaking. However, it also raises significant secur...
Wide coverage and high-precision rural household wealth data is an important support for the effective connection between the national macro rural r...
We introduce Long-VITA, a simple yet effective large multi-modal model for long-context visual-language understanding tasks. It is adept at concurre...
The perspective of developing trustworthy AI for critical applications in science and engineering requires machine learning techniques that are capa...
The integration of renewable energy into electricity markets poses significant challenges to price stability and increases the complexity of market ...
TerraQ is a spatiotemporal question-answering engine for satellite image archives. It is a natural language processing system that is built to proce...
Recently computer-aided diagnosis has demonstrated promising performance, effectively alleviating the workload of clinicians. However, the inherent ...
Large language models (LLMs) have shown impressive capabilities in natural language processing tasks, including dialogue generation. This research a...