Heart Transplantation

Do We Really Need Curated Malicious Data for Safety Alignment in Multi-modal Large Language Models?

Multi-modal large language models (MLLMs) have made significant progress, yet their safety alignment remains limited. Typically, current open-source MLLMs rely on the alignment inherited from their language module to avoid harmful generations. However, the lack of safety measures specifically designed for multi-modal inputs creates an alignment gap, leaving MLLMs vulnerable to vision-domain atta...

Localization Meets Uncertainty: Uncertainty-Aware Multi-Modal Localization

Reliable localization is critical for robot navigation in complex indoor environments. In this paper, we propose an uncertainty-aware localization method that enhances the reliability of localization outputs without modifying the prediction model itself. This study introduces a percentile-based rejection strategy that filters out unreliable 3-DoF pose predictions based on aleatoric and epistemic...

GMAI-VL-R1: Harnessing Reinforcement Learning for Multimodal Medical Reasoning

Recent advances in general medical AI have made significant strides, but existing models often lack the reasoning capabilities needed for complex me...

Thinking Longer, Not Larger: Enhancing Software Engineering Agents via Scaling Test-Time Compute

Recent advancements in software engineering agents have demonstrated promising capabilities in automating program improvements. However, their relia...

Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive Tasks

Recent advances in deep thinking models have demonstrated remarkable reasoning capabilities on mathematical and coding tasks. However, their effecti...

The Greatest Good Benchmark: Measuring LLMs' Alignment with Utilitarian Moral Dilemmas

The question of how to make decisions that maximise the well-being of all persons is very relevant to design language models that are beneficial to ...

Why do Opinions and Actions Diverge? A Dynamic Framework to Explore the Impact of Subjective Norms

Socio-psychological studies have identified a common phenomenon where an individual's public actions do not necessarily coincide with their private ...

OSLoPrompt: Bridging Low-Supervision Challenges and Open-Set Domain Generalization in CLIP

We introduce Low-Shot Open-Set Domain Generalization (LSOSDG), a novel paradigm unifying low-shot learning with open-set domain generalization (ODG)...

Is there a future for AI without representation?

This paper investigates the prospects of AI without representation in general, and the proposals of Rodney Brooks in particular. What turns out to b...

Open-Set Plankton Recognition

This paper considers open-set recognition (OSR) of plankton images. Plankton include a diverse range of microscopic aquatic organisms that have an i...

KidneyTalk-open: No-code Deployment of a Private Large Language Model with Medical Documentation-Enhanced Knowledge Database for Kidney Disease

Privacy-preserving medical decision support for kidney disease requires localized deployment of large language models (LLMs) while maintaining clini...

Identifying Risk Factors for Graft Failure due to Chronic Rejection < 15 Years Post-Transplant in Pediatric Kidney Transplants Using Random Forest Machine-Learning Techniques.

BACKGROUND: Chronic rejection forms the leading cause of late graft loss in pediatric kidney transplant recipients. Despite improvement in short-term ...

Hybrid Retrieval for Hallucination Mitigation in Large Language Models: A Comparative Analysis

Large Language Models (LLMs) excel in language comprehension and generation but are prone to hallucinations, producing factually incorrect or unsupp...

EXACT-CT: EXplainable Analysis for Crohn's and Tuberculosis using CT

Crohn's disease and intestinal tuberculosis share many overlapping features such as clinical, radiological, endoscopic, and histological features - ...

Visual Reasoning Evaluation of Grok, Deepseek Janus, Gemini, Qwen, Mistral, and ChatGPT

Traditional evaluations of multimodal large language models (LLMs) have been limited by their focus on single-image reasoning, failing to assess cru...

Rapid Parameter Inference with Uncertainty Quantification for a Radiological Plume Source Identification Problem

In the event of a nuclear accident, or the detonation of a radiological dispersal device, quickly locating the source of the accident or blast is im...

Enhancing Cognition and Explainability of Multimodal Foundation Models with Self-Synthesized Data

Large Multimodal Models (LMMs), or Vision-Language Models (VLMs), have shown impressive capabilities in a wide range of visual tasks. However, they ...

Nonlinear Feedback Linearization and LQG/LTR Control: A Comparative Study for a Single-Machine Infinite-Bus System

This paper presents a comparative study of three advanced control strategies for a single-machine infinite-bus (SMIB) system: the nonlinear feedback...

Detection and classification of glomerular lesions in kidney graft biopsies using 2-stage deep learning approach.

Acute allograft rejection in patients undergoing renal transplantation is diagnosed through histopathological analysis of renal graft biopsies, which ...

Leveraging Registers in Vision Transformers for Robust Adaptation

Vision Transformers (ViTs) have shown success across a variety of tasks due to their ability to capture global image representations. Recent studies...