Care of terminally ill / Palliative care

ORMind: A Cognitive-Inspired End-to-End Reasoning Framework for Operations Research

Operations research (OR) is widely deployed to solve critical decision-making problems with complex objectives and constraints, impacting manufacturing, logistics, finance, and healthcare outcomes. While Large Language Models (LLMs) have shown promising results in various domains, their practical application in industry-relevant operations research (OR) problems presents significant challenges a...

EB-YOLO:An efficient and lightweight blood cell detector based on the YOLO algorithm.

Blood cell detection is an important part of medical diagnosis. Object detection is trending for blood cell analysis, with research focusing on high-precision neural network models. However, these models have complex architectures and high computational costs. They cannot achieve rapid detection on low-end devices. Although lightweight models can greatly enhance the detection speed and achieve the...

A "Wenlu" Brain System for Multimodal Cognition and Embodied Decision-Making: A Secure New Architecture for Deep Integration of Foundation Models and Domain Knowledge

With the rapid penetration of artificial intelligence across industries and scenarios, a key challenge in building the next-generation intelligent c...

Chameleon: A MatMul-Free Temporal Convolutional Network Accelerator for End-to-End Few-Shot and Continual Learning from Sequential Data

On-device learning at the edge enables low-latency, private personalization with improved long-term robustness and reduced maintenance costs. Yet, a...

Generative AI for Urban Design: A Stepwise Approach Integrating Human Expertise with Multimodal Diffusion Models

Urban design is a multifaceted process that demands careful consideration of site-specific constraints and collaboration among diverse professionals...

Hold My Beer: Learning Gentle Humanoid Locomotion and End-Effector Stabilization Control

Can your humanoid walk up and hand you a full cup of beer, without spilling a drop? While humanoids are increasingly featured in flashy demos like d...

S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Modelwith Spatio-Temporal Visual Representation

The latest advancements in multi-modal large language models (MLLMs) have spurred a strong renewed interest in end-to-end motion planning approaches...

An end-to-end mass spectrometry data classification model with a unified architecture.

Mass spectrometry, known for its high sensitivity, selectivity, rich structural information, and rapid analysis capabilities, is widely used in diseas...

Dc-EEMF: Pushing depth-of-field limit of photoacoustic microscopy via decision-level constrained learning

Photoacoustic microscopy holds the potential to measure biomarkers' structural and functional status without labels, which significantly aids in com...

Robust and Annotation-Free Wound Segmentation on Noisy Real-World Pressure Ulcer Images: Towards Automated DESIGN-R\textsuperscript{\textregistered} Assessment

Purpose: Accurate wound segmentation is essential for automated DESIGN-R scoring. However, existing models such as FUSegNet, which are trained prima...

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging

Deep-unrolling and plug-and-play (PnP) approaches have become the de-facto standard solvers for single-pixel imaging (SPI) inverse problem. PnP appr...

Learning coordinated badminton skills for legged manipulators

Coordinating the motion between lower and upper limbs and aligning limb control with perception are substantial challenges in robotics, particularly...

3DGS Compression with Sparsity-guided Hierarchical Transform Coding

3D Gaussian Splatting (3DGS) has gained popularity for its fast and high-quality rendering, but it has a very large memory footprint incurring high ...

Test-Time Alignment of Discrete Diffusion Models with Sequential Monte Carlo

Discrete diffusion models have become highly effective across various domains. However, real-world applications often require the generative process...

RAG-Zeval: Towards Robust and Interpretable Evaluation on RAG Responses through End-to-End Rule-Guided Reasoning

Robust evaluation is critical for deploying trustworthy retrieval-augmented generation (RAG) systems. However, current LLM-based evaluation framewor...

Large-Area Fabrication-aware Computational Diffractive Optics

Differentiable optics, as an emerging paradigm that jointly optimizes optics and (optional) image processing algorithms, has made innovative optical...

EaqVLA: Encoding-aligned Quantization for Vision-Language-Action Models

With the development of Embodied Artificial intelligence, the end-to-end control policy such as Vision-Language-Action (VLA) model has become the ma...

Visual Product Graph: Bridging Visual Products And Composite Images For End-to-End Style Recommendations

Retrieving semantically similar but visually distinct contents has been a critical capability in visual search systems. In this work, we aim to tack...

Sci-Fi: Symmetric Constraint for Frame Inbetweening

Frame inbetweening aims to synthesize intermediate video sequences conditioned on the given start and end frames. Current state-of-the-art methods m...

BIPNN: Learning to Solve Binary Integer Programming via Hypergraph Neural Networks

Binary (0-1) integer programming (BIP) is pivotal in scientific domains requiring discrete decision-making. As the advance of AI computing, recent w...