Staffing & Scheduling

Pairwise Similarity Regularization for Semi-supervised Graph Medical Image Segmentation

With fully leveraging the value of unlabeled data, semi-supervised medical image segmentation algorithms significantly reduces the limitation of limited labeled data, achieving a significant improvement in accuracy. However, the distributional shift between labeled and unlabeled data weakens the utilization of information from the labeled data. To alleviate the problem, we propose a graph networ...

Sakshm AI: Advancing AI-Assisted Coding Education for Engineering Students in India Through Socratic Tutoring and Comprehensive Feedback

The advent of Large Language Models (LLMs) is reshaping education, particularly in programming, by enhancing problem-solving, enabling personalized feedback, and supporting adaptive learning. Existing AI tools for programming education struggle with key challenges, including the lack of Socratic guidance, direct code generation, limited context retention, minimal adaptive feedback, and the need ...

ECLARE: Efficient cross-planar learning for anisotropic resolution enhancement

In clinical imaging, magnetic resonance (MR) image volumes are often acquired as stacks of 2D slices with decreased scan times, improved signal-to-n...

Integrating LLMs in Gamified Systems

In this work, a thorough mathematical framework for incorporating Large Language Models (LLMs) into gamified systems is presented with an emphasis o...

FlowTok: Flowing Seamlessly Across Text and Image Tokens

Bridging different modalities lies at the heart of cross-modality generation. While conventional approaches treat the text modality as a conditionin...

Enhance Exploration in Safe Reinforcement Learning with Contrastive Representation Learning

In safe reinforcement learning, agent needs to balance between exploration actions and safety constraints. Following this paradigm, domain transfer ...

Channel-wise Noise Scheduled Diffusion for Inverse Rendering in Indoor Scenes

We propose a diffusion-based inverse rendering framework that decomposes a single RGB image into geometry, material, and lighting. Inverse rendering...

Long-horizon Visual Instruction Generation with Logic and Attribute Self-reflection

Visual instructions for long-horizon tasks are crucial as they intuitively clarify complex concepts and enhance retention across extended steps. Dir...

Evaluating Multi-Instance DNN Inferencing on Multiple Accelerators of an Edge Device

Edge devices like Nvidia Jetson platforms now offer several on-board accelerators -- including GPU CUDA cores, Tensor Cores, and Deep Learning Accel...

Alias-Free Latent Diffusion Models:Improving Fractional Shift Equivariance of Diffusion Latent Space

Latent Diffusion Models (LDMs) are known to have an unstable generation process, where even small perturbations or shifts in the input noise can lea...

Differential Privacy Personalized Federated Learning Based on Dynamically Sparsified Client Updates

Personalized federated learning is extensively utilized in scenarios characterized by data heterogeneity, facilitating more efficient and automated ...

Visual Attention Graph

Visual attention plays a critical role when our visual system executes active visual tasks by interacting with the physical scene. However, how to e...

AI-native Memory 2.0: Second Me

Human interaction with the external world fundamentally involves the exchange of personal memory, whether with other individuals, websites, applicat...

H3PIMAP: A Heterogeneity-Aware Multi-Objective DNN Mapping Framework on Electronic-Photonic Processing-in-Memory Architectures

The future of artificial intelligence (AI) acceleration demands a paradigm shift beyond the limitations of purely electronic or photonic architectur...

A LongFormer-Based Framework for Accurate and Efficient Medical Text Summarization

This paper proposes a medical text summarization method based on LongFormer, aimed at addressing the challenges faced by existing models when proces...

Red Team Diffuser: Exposing Toxic Continuation Vulnerabilities in Vision-Language Models via Reinforcement Learning

The growing deployment of large Vision-Language Models (VLMs) exposes critical safety gaps in their alignment mechanisms. While existing jailbreak s...

Human-AI Experience in Integrated Development Environments: A Systematic Literature Review

The integration of Artificial Intelligence (AI) into Integrated Development Environments (IDEs) is reshaping software development, fundamentally alt...

Pathological Prior-Guided Multiple Instance Learning For Mitigating Catastrophic Forgetting in Breast Cancer Whole Slide Image Classification

In histopathology, intelligent diagnosis of Whole Slide Images (WSIs) is essential for automating and objectifying diagnoses, reducing the workload ...

Bridging Classical and Quantum String Matching: A Computational Reformulation of Bit-Parallelism

String matching is a fundamental problem in computer science, with critical applications in text retrieval, bioinformatics, and data analysis. Among...

Data-Efficient Generalization for Zero-shot Composed Image Retrieval

Zero-shot Composed Image Retrieval (ZS-CIR) aims to retrieve the target image based on a reference image and a text description without requiring in...