Medicare

Can We Edit LLMs for Long-Tail Biomedical Knowledge?

Knowledge editing has emerged as an effective approach for updating large language models (LLMs) by modifying their internal knowledge. However, their application to the biomedical domain faces unique challenges due to the long-tailed distribution of biomedical knowledge, where rare and infrequent information is prevalent. In this paper, we conduct the first comprehensive study to investigate th...

SIO-Mapper: A Framework for Lane-Level HD Map Construction Using Satellite Images and OpenStreetMap with No On-Site Visits

High-definition (HD) maps, particularly those containing lane-level information regarded as ground truth, are crucial for vehicle localization research. Traditionally, constructing HD maps requires highly accurate sensor measurements collection from the target area, followed by manual annotation to assign semantic information. Consequently, HD maps are limited in terms of geographic coverage. To...

DiverseFlow: Sample-Efficient Diverse Mode Coverage in Flows

Many real-world applications of flow-based generative models desire a diverse set of samples that cover multiple modes of the target distribution. H...

Kimi-VL Technical Report

We present Kimi-VL, an efficient open-source Mixture-of-Experts (MoE) vision-language model (VLM) that offers advanced multimodal reasoning, long-co...

Jointly-optimized Trajectory Generation and Camera Control for 3D Coverage Planning

This work proposes a jointly optimized trajectory generation and camera control approach, enabling an autonomous agent, such as an unmanned aerial v...

Leveraging State Space Models in Long Range Genomics

Long-range dependencies are critical for understanding genomic structure and function, yet most conventional methods struggle with them. Widely adop...

Adaptive path planning for efficient object search by UAVs in agricultural fields

This paper presents an adaptive path planner for object search in agricultural fields using UAVs. The path planner uses a high-altitude coverage fli...

Re-thinking Temporal Search for Long-Form Video Understanding

Efficiently understanding long-form videos remains a significant challenge in computer vision. In this work, we revisit temporal search paradigms fo...

Conformal uncertainty quantification to evaluate predictive fairness of foundation AI model for skin lesion classes across patient demographics

Deep learning based diagnostic AI systems based on medical images are starting to provide similar performance as human experts. However these data h...

Learning to Reason for Long-Form Story Generation

Generating high-quality stories spanning thousands of tokens requires competency across a variety of skills, from tracking plot and character arcs t...

Post-Incorporating Code Structural Knowledge into LLMs via In-Context Learning for Code Translation

Code translation migrates codebases across programming languages. Recently, large language models (LLMs) have achieved significant advancements in s...

M-DocSum: Do LVLMs Genuinely Comprehend Interleaved Image-Text in Document Summarization?

We investigate a critical yet under-explored question in Large Vision-Language Models (LVLMs): Do LVLMs genuinely comprehend interleaved image-text ...

Utsarjan: A smartphone App for providing kidney care and real-time assistance to children with nephrotic syndrome

Background Telemedicine has the potential to provide secure and cost-effective healthcare at the touch of a button. Nephrotic syndrome is a chronic ...

Patients Speak, AI Listens: LLM-based Analysis of Online Reviews Uncovers Key Drivers for Urgent Care Satisfaction

Investigating the public experience of urgent care facilities is essential for promoting community healthcare development. Traditional survey method...

Beyond Words: Advancing Long-Text Image Generation via Multimodal Autoregressive Models

Recent advancements in autoregressive and diffusion models have led to strong performance in image generation with short scene text words. However, ...

LRSCLIP: A Vision-Language Foundation Model for Aligning Remote Sensing Image with Longer Text

This study addresses the technical bottlenecks in handling long text and the "hallucination" issue caused by insufficient short text information in ...

ELM: Ensemble of Language Models for Predicting Tumor Group from Pathology Reports

Population-based cancer registries (PBCRs) face a significant bottleneck in manually extracting data from unstructured pathology reports, a process ...

CHOrD: Generation of Collision-Free, House-Scale, and Organized Digital Twins for 3D Indoor Scenes with Controllable Floor Plans and Optimal Layouts

We introduce CHOrD, a novel framework for scalable synthesis of 3D indoor scenes, designed to create house-scale, collision-free, and hierarchically...

Systematic Classification of Studies Investigating Social Media Conversations about Long COVID Using a Novel Zero-Shot Transformer Framework

Long COVID continues to challenge public health by affecting a considerable number of individuals who have recovered from acute SARS-CoV-2 infection...

Context-Aware Rule Mining Using a Dynamic Transformer-Based Framework

This study proposes a dynamic rule data mining algorithm based on an improved Transformer architecture, aiming to improve the accuracy and efficienc...