Identifying and Reporting Dependent Adult abuse

Aerial Vision-and-Language Navigation with Grid-based View Selection and Map Construction

Aerial Vision-and-Language Navigation (Aerial VLN) aims to obtain an unmanned aerial vehicle agent to navigate aerial 3D environments following human instruction. Compared to ground-based VLN, aerial VLN requires the agent to decide the next action in both horizontal and vertical directions based on the first-person view observations. Previous methods struggle to perform well due to the longer n...

$(\varepsilon, δ)$ Considered Harmful: Best Practices for Reporting Differential Privacy Guarantees

Current practices for reporting the level of differential privacy (DP) guarantees for machine learning (ML) algorithms provide an incomplete and potentially misleading picture of the guarantees and make it difficult to compare privacy levels across different settings. We argue for using Gaussian differential privacy (GDP) as the primary means of communicating DP guarantees in ML, with the full p...

Natural Humanoid Robot Locomotion with Generative Motion Prior

Natural and lifelike locomotion remains a fundamental challenge for humanoid robots to interact with human society. However, previous methods either...

"Principal Components" Enable A New Language of Images

We introduce a novel visual tokenization framework that embeds a provable PCA-like structure into the latent token space. While existing visual toke...

GAS-NeRF: Geometry-Aware Stylization of Dynamic Radiance Fields

Current 3D stylization techniques primarily focus on static scenes, while our world is inherently dynamic, filled with moving objects and changing e...

Personalized Code Readability Assessment: Are We There Yet?

Unreadable code could be a breeding ground for errors. Thus, previous work defined approaches based on machine learning to automatically assess code...

SeCap: Self-Calibrating and Adaptive Prompts for Cross-view Person Re-Identification in Aerial-Ground Networks

When discussing the Aerial-Ground Person Re-identification (AGPReID) task, we face the main challenge of the significant appearance variations cause...

MPTSNet: Integrating Multiscale Periodic Local Patterns and Global Dependencies for Multivariate Time Series Classification

Multivariate Time Series Classification (MTSC) is crucial in extensive practical applications, such as environmental monitoring, medical EEG analysi...

Interactive Segmentation and Report Generation for CT Images

Automated CT report generation plays a crucial role in improving diagnostic accuracy and clinical workflow efficiency. However, existing methods lac...

V$^2$Dial: Unification of Video and Visual Dialog via Multimodal Experts

We present V$^2$Dial - a novel expert-based model specifically geared towards simultaneously handling image and video input data for multimodal conv...

A Lightweight Deep Exclusion Unfolding Network for Single Image Reflection Removal

Single Image Reflection Removal (SIRR) is a canonical blind source separation problem and refers to the issue of separating a reflection-contaminate...

Soybean Disease Detection via Interpretable Hybrid CNN-GNN: Integrating MobileNetV2 and GraphSAGE with Cross-Modal Attention

Soybean leaf disease detection is critical for agricultural productivity but faces challenges due to visually similar symptoms and limited interpret...

Value of Using a Generative AI Model in Chest Radiography Reporting: A Reader Study.

Background Multimodal generative artificial intelligence (AI) technologies can produce preliminary radiology reports, and validation with reader studi...

Parallel-Learning of Invariant and Tempo-variant Attributes of Single-Lead Cardiac Signals: PLITA

Wearable sensing devices, such as Holter monitors, will play a crucial role in the future of digital health. Unsupervised learning frameworks such a...

Unleashing the Potential of Two-Tower Models: Diffusion-Based Cross-Interaction for Large-Scale Matching

Two-tower models are widely adopted in the industrial-scale matching stage across a broad range of application domains, such as content recommendati...

Optimizing functional brain network analysis by incorporating nonlinear factors and frequency band selection with machine learning models.

The accurate assessment of the brain's functional network is seen as crucial for the understanding of complex relationships between different brain re...

The NeRF Signature: Codebook-Aided Watermarking for Neural Radiance Fields

Neural Radiance Fields (NeRF) have been gaining attention as a significant form of 3D content representation. With the proliferation of NeRF-based c...

Symmetrical Visual Contrastive Optimization: Aligning Vision-Language Models with Minimal Contrastive Images

Recent studies have shown that Large Vision-Language Models (VLMs) tend to neglect image content and over-rely on language-model priors, resulting i...

MGFI-Net: A Multi-Grained Feature Integration Network for Enhanced Medical Image Segmentation

Medical image segmentation plays a crucial role in various clinical applications. A major challenge in medical image segmentation is achieving accur...

From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms

When an individual reports a negative interaction with some system, how can their personal experience be contextualized within broader patterns of s...