Urinary Incontinence

NumScout: Unveiling Numerical Defects in Smart Contracts using LLM-Pruning Symbolic Execution

In recent years, the Ethereum platform has witnessed a proliferation of smart contracts, accompanied by exponential growth in total value locked (TVL). High-TVL smart contracts often require complex numerical computations, particularly in mathematical financial models used by many decentralized applications (DApps). Improper calculations can introduce numerical defects, posing potential security...

Psycholinguistic Analyses in Software Engineering Text: A Systematic Literature Review

Context: A deeper understanding of human factors in software engineering (SE) is essential for improving team collaboration, decision-making, and productivity. Communication channels like code reviews and chats provide insights into developers' psychological and emotional states. While large language models excel at text analysis, they often lack transparency and precision. Psycholinguistic tool...

Deep Robust Reversible Watermarking

Robust Reversible Watermarking (RRW) enables perfect recovery of cover images and watermarks in lossless channels while ensuring robust watermark ex...

Online Pseudo-average Shifting Attention(PASA) for Robust Low-precision LLM Inference: Algorithms and Numerical Analysis

Attention calculation is extremely time-consuming for long-sequence inference tasks, such as text or image/video generation, in large models. To acc...

Robustness tests for biomedical foundation models should tailor to specification

Existing regulatory frameworks for biomedical AI include robustness as a key component but lack detailed implementational guidance. The recent rise ...

Great Power Brings Great Responsibility: Personalizing Conversational AI for Diverse Problem-Solvers

Newcomers onboarding to Open Source Software (OSS) projects face many challenges. Large Language Models (LLMs), like ChatGPT, have emerged as potent...

Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help?

Functional brain connectome is crucial for deciphering the neural mechanisms underlying cognitive functions and neurological disorders. Graph deep l...

Graph Feedback Bandits on Similar Arms: With and Without Graph Structures

In this paper, we study the stochastic multi-armed bandit problem with graph feedback. Motivated by applications in clinical trials and recommendati...

Three-precision iterative refinement with parameter regularization and prediction for solving large sparse linear systems

This study presents a novel mixed-precision iterative refinement algorithm, GADI-IR, within the general alternating-direction implicit (GADI) framew...

Risking your Tail: Modeling Individual Differences in Risk-sensitive Exploration using Bayes Adaptive Markov Decision Processes

Novelty is a double-edged sword for agents and animals alike: they might benefit from untapped resources or face unexpected costs or dangers such as p...

APDeeM: A machine Learning strategy towards Effective Peptide Vaccine Candidates Identification against Different Types of Viruses

Viral infections pose significant global health challenges, underscoring the urgent need for improved medications. Nevertheless, traditional medicinal...

A groove brain-music interface for enhancing individual experience of urge to move

When we listen to music, we often feel a pleasurable urge to move to music, known as groove. While previous studies have identified musical features t...

Artificial Intelligence Approximates Human Affect Ratings of Cannabis Images

Cannabis imagery is proliferating online and can elicit affective responses related to use. Scalable tools are needed to evaluate how this proliferati...

Multi-Armed Bandit Approach for Optimizing Training on Synthetic Data

Supervised machine learning methods require large-scale training datasets to perform well in practice. Synthetic data has been showing great progres...

Robust Steganography with Boundary-Preserving Overflow Alleviation and Adaptive Error Correction

With the rapid evolution of the Internet, the vast amount of data has created opportunities for fostering the development of steganographic techniqu...

Accelerating Large Language Model Training with 4D Parallelism and Memory Consumption Estimator

In large language model (LLM) training, several parallelization strategies, including Tensor Parallelism (TP), Pipeline Parallelism (PP), Data Paral...

Infiltrating the Sky: Data Delay and Overflow Attacks in Earth Observation Constellations

Low Earth Orbit (LEO) Earth Observation (EO) satellites have changed the way we monitor Earth. Acting like moving cameras, EO satellites are formed ...

Data-driven Modeling of Combined Sewer Systems for Urban Sustainability: An Empirical Evaluation

Climate change poses complex challenges, with extreme weather events becoming increasingly frequent and difficult to model. Examples include the dyn...

Jailbreaking Text-to-Image Models with LLM-Based Agents

Recent advancements have significantly improved automated task-solving capabilities using autonomous agents powered by large language models (LLMs)....

Understanding Auditory Evoked Brain Signal via Physics-informed Embedding Network with Multi-Task Transformer

In the fields of brain-computer interaction and cognitive neuroscience, effective decoding of auditory signals from task-based functional magnetic r...