Clinical Trials

SafeCFG: Redirecting Harmful Classifier-Free Guidance for Safe Generation

Diffusion models (DMs) have demonstrated exceptional performance in text-to-image (T2I) tasks, leading to their widespread use. With the introduction of classifier-free guidance (CFG), the quality of images generated by DMs is improved. However, DMs can generate more harmful images by maliciously guiding the image generation process through CFG. Some safe guidance methods aim to mitigate the ris...

Mobilizing Waldo: Evaluating Multimodal AI for Public Mobilization

Advancements in multimodal Large Language Models (LLMs), such as OpenAI's GPT-4o, offer significant potential for mediating human interactions across various contexts. However, their use in areas such as persuasion, influence, and recruitment raises ethical and security concerns. To evaluate these models ethically in public influence and persuasion scenarios, we developed a prompting strategy us...

Evaluation of LLM Vulnerabilities to Being Misused for Personalized Disinformation Generation

The capabilities of recent large language models (LLMs) to generate high-quality content indistinguishable by humans from human-written texts rises ...

SafetyDPO: Scalable Safety Alignment for Text-to-Image Generation

Text-to-image (T2I) models have become widespread, but their limited safety guardrails expose end users to harmful content and potentially allow for...

Which cycling environment appears safer? Learning cycling safety perceptions from pairwise image comparisons

Cycling is critical for cities to transition to more sustainable transport modes. Yet, safety concerns remain a critical deterrent for individuals t...

The effectiveness of care robots in alleviating physical burden and pain for caregivers: Non-randomized prospective interventional study - Preliminary study.

BACKGROUND: Caregiver burden significantly affects both patients and caregivers but is often overlooked in clinical practice. Physical and emotional s...

From Bench to Bedside: A Review of Clinical Trials in Drug Discovery and Development

Clinical trials are an indispensable part of the drug development process, bridging the gap between basic research and clinical application. During ...

Multilevel randomized quasi-Monte Carlo estimator for nested integration

Nested integration problems arise in various scientific and engineering applications, including Bayesian experimental design, financial risk assessm...

Learning k-Inductive Control Barrier Certificates for Unknown Nonlinear Dynamics Beyond Polynomials

This work is concerned with synthesizing safety controllers for discrete-time nonlinear systems beyond polynomials with unknown mathematical models ...

Advancing clinical trial outcomes using deep learning and predictive modelling: bridging precision medicine and patient-centered care

The integration of artificial intelligence [AI] into clinical trials has revolutionized the process of drug development and personalized medicine. A...

EMOv2: Pushing 5M Vision Model Frontier

This work focuses on developing parameter-efficient and lightweight models for dense predictions while trading off parameters, FLOPs, and performanc...

SafeWorld: Geo-Diverse Safety Alignment

In the rapidly evolving field of Large Language Models (LLMs), ensuring safety is a crucial and widely discussed topic. However, existing works ofte...

Precise, Fast, and Low-cost Concept Erasure in Value Space: Orthogonal Complement Matters

Recent success of text-to-image (T2I) generation and its increasing practical applications, enabled by diffusion models, require urgent consideratio...

Employee Well-being in the Age of AI: Perceptions, Concerns, Behaviors, and Outcomes

The growing integration of Artificial Intelligence (AI) into Human Resources (HR) processes has transformed the way organizations manage recruitment...

Incorporating System-level Safety Requirements in Perception Models via Reinforcement Learning

Perception components in autonomous systems are often developed and optimized independently of downstream decision-making and control components, re...

Efficient Algorithms for Low Tubal Rank Tensor Approximation with Applications

In this paper we propose efficient randomized fixed-precision techniques for low tubal rank approximation of tensors. The proposed methods are faste...

Randomized algorithms for Kroncecker tensor decomposition and applications

This paper proposes fast randomized algorithms for computing the Kronecker Tensor Decomposition (KTD). The proposed algorithms can decompose a given...

The use of large language models to enhance cancer clinical trial educational materials

Cancer clinical trials often face challenges in recruitment and engagement due to a lack of participant-facing informational and educational resourc...

AR-Facilitated Safety Inspection and Fall Hazard Detection on Construction Sites

Together with industry experts, we are exploring the potential of head-mounted augmented reality to facilitate safety inspections on high-rise const...

DFRot: Achieving Outlier-Free and Massive Activation-Free for Rotated LLMs with Refined Rotation

Rotating the activation and weight matrices to reduce the influence of outliers in large language models (LLMs) has recently attracted significant a...