Surveys

QDCNN: Quantum Deep Learning for Enhancing Safety and Reliability in Autonomous Transportation Systems

In transportation cyber-physical systems (CPS), ensuring safety and reliability in real-time decision-making is essential for successfully deploying autonomous vehicles and intelligent transportation networks. However, these systems face significant challenges, such as computational complexity and the ability to handle ambiguous inputs like shadows in complex environments. This paper introduces ...

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 unsupported outputs. Retrieval Augmented Generation (RAG) systems address this issue by grounding LLM responses with external knowledge. This study evaluates the relationship between retriever effectiveness and hallucination reduction in LLMs using three r...

Merging Clinical Knowledge into Large Language Models for Medical Research and Applications: A Survey

Clinical knowledge is the collection of information learned from studies on the causes, prognosis, diagnosis, and treatment of diseases. This type o...

Collective Reasoning Among LLMs A Framework for Answer Validation Without Ground Truth

We present a collaborative framework where multiple large language models, namely GPT-4-0125-preview, Meta-LLaMA-3-70B-Instruct, Claude-3-Opus, and ...

Explainable AI for Clinical Outcome Prediction: A Survey of Clinician Perceptions and Preferences

Explainable AI (XAI) techniques are necessary to help clinicians make sense of AI predictions and integrate predictions into their decision-making w...

Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation

Autoregressive (AR) modeling, known for its next-token prediction paradigm, underpins state-of-the-art language and visual generative models. Tradit...

Learning to Generalize without Bias for Open-Vocabulary Action Recognition

Leveraging the effective visual-text alignment and static generalizability from CLIP, recent video learners adopt CLIP initialization with further r...

Scalability of the second-order reliability method for stochastic differential equations with multiplicative noise

We show how to efficiently compute asymptotically sharp estimates of extreme event probabilities in stochastic differential equations (SDEs) with sm...

The erasure of intensive livestock farming in text-to-image generative AI

Generative AI (e.g., ChatGPT) is increasingly integrated into people's daily lives. While it is known that AI perpetuates biases against marginalize...

Revealing Treatment Non-Adherence Bias in Clinical Machine Learning Using Large Language Models

Machine learning systems trained on electronic health records (EHRs) increasingly guide treatment decisions, but their reliability depends on the cr...

FairGen: Controlling Sensitive Attributes for Fair Generations in Diffusion Models via Adaptive Latent Guidance

Text-to-image diffusion models often exhibit biases toward specific demographic groups, such as generating more males than females when prompted to ...

Defining bias in AI-systems: Biased models are fair models

The debate around bias in AI systems is central to discussions on algorithmic fairness. However, the term bias often lacks a clear definition, despi...

Assessing Large Language Models in Agentic Multilingual National Bias

Large Language Models have garnered significant attention for their capabilities in multilingual natural language processing, while studies on risks...

Tip of the Tongue Query Elicitation for Simulated Evaluation

Tip-of-the-tongue (TOT) search occurs when a user struggles to recall a specific identifier, such as a document title. While common, existing search...

HybridLinker: Topology-Guided Posterior Sampling for Enhanced Diversity and Validity in 3D Molecular Linker Generation

Linker generation is critical in drug discovery applications such as lead optimization and PROTAC design, where molecular fragments are assembled in...

A survey of datasets for computer vision in agriculture

In agricultural research, there has been a recent surge in the amount of Computer Vision (CV) focused work. But unlike general CV research, large hi...

Fair Foundation Models for Medical Image Analysis: Challenges and Perspectives

Ensuring equitable Artificial Intelligence (AI) in healthcare demands systems that make unbiased decisions across all demographic groups, bridging t...

FedBM: Stealing Knowledge from Pre-trained Language Models for Heterogeneous Federated Learning

Federated learning (FL) has shown great potential in medical image computing since it provides a decentralized learning paradigm that allows multipl...

Uncertainty Quantification of Large Language Models through Multi-Dimensional Responses

Large Language Models (LLMs) have demonstrated remarkable capabilities across various tasks due to large training datasets and powerful transformer ...

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...