Psychiatry

Schizophrenia

Latest AI and machine learning research in schizophrenia for healthcare professionals.

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SegSub: Evaluating Robustness to Knowledge Conflicts and Hallucinations in Vision-Language Models

Vision language models (VLM) demonstrate sophisticated multimodal reasoning yet are prone to hallu...

High-Fidelity Novel View Synthesis via Splatting-Guided Diffusion

Despite recent advances in Novel View Synthesis (NVS), generating high-fidelity views from single ...

CutPaste&Find: Efficient Multimodal Hallucination Detector with Visual-aid Knowledge Base

Large Vision-Language Models (LVLMs) have demonstrated impressive multimodal reasoning capabilitie...

Lost in Transcription, Found in Distribution Shift: Demystifying Hallucination in Speech Foundation Models

Speech foundation models trained at a massive scale, both in terms of model and data size, result ...

LanP: Rethinking the Impact of Language Priors in Large Vision-Language Models

Large Vision-Language Models (LVLMs) have shown impressive performance in various tasks. However, ...

A Survey of LLM-based Agents in Medicine: How far are we from Baymax?

Large Language Models (LLMs) are transforming healthcare through the development of LLM-based agen...

HuDEx: Integrating Hallucination Detection and Explainability for Enhancing the Reliability of LLM responses

Recent advances in large language models (LLMs) have shown promising improvements, often surpassin...

DeepSeek on a Trip: Inducing Targeted Visual Hallucinations via Representation Vulnerabilities

Multimodal Large Language Models (MLLMs) represent the cutting edge of AI technology, with DeepSee...

Enhancing Knowledge Graph Construction: Evaluating with Emphasis on Hallucination, Omission, and Graph Similarity Metrics

Recent advancements in large language models have demonstrated significant potential in the automa...

Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration

Large Vision-Language Models (LVLMs) exhibit impressive multimodal reasoning capabilities but rema...

MJ-VIDEO: Fine-Grained Benchmarking and Rewarding Video Preferences in Video Generation

Recent advancements in video generation have significantly improved the ability to synthesize vide...

Assessing the use of Diffusion models for motion artifact correction in brain MRI

Magnetic Resonance Imaging generally requires long exposure times, while being sensitive to patien...

MINT: Mitigating Hallucinations in Large Vision-Language Models via Token Reduction

Hallucination has been a long-standing and inevitable problem that hinders the application of Larg...

Towards Privacy-aware Mental Health AI Models: Advances, Challenges, and Opportunities

Mental illness is a widespread and debilitating condition with substantial societal and personal c...

CHiP: Cross-modal Hierarchical Direct Preference Optimization for Multimodal LLMs

Multimodal Large Language Models (MLLMs) still struggle with hallucinations despite their impressi...

Scaling Large Vision-Language Models for Enhanced Multimodal Comprehension In Biomedical Image Analysis

Large language models (LLMs) have demonstrated immense capabilities in understanding textual data ...

Mirage in the Eyes: Hallucination Attack on Multi-modal Large Language Models with Only Attention Sink

Fusing visual understanding into language generation, Multi-modal Large Language Models (MLLMs) ar...

Evaluating Hallucination in Large Vision-Language Models based on Context-Aware Object Similarities

Despite their impressive performance on multi-modal tasks, large vision-language models (LVLMs) te...

Measuring and Mitigating Hallucinations in Vision-Language Dataset Generation for Remote Sensing

Vision language models have achieved impressive results across various fields. However, adoption i...

Comprehensive Modeling and Question Answering of Cancer Clinical Practice Guidelines using LLMs

The updated recommendations on diagnostic procedures and treatment pathways for a medical conditio...

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