Psychiatry

Schizophrenia

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

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SycoPhantasy: Quantifying Sycophancy and Hallucination in Small Open Weight VLMs for Vision-Language Scoring of Fantasy Characters

Vision-language models (VLMs) are increasingly deployed as evaluators in tasks requiring nuanced ima...

CGC: Compositional Grounded Contrast for Fine-Grained Multi-Image Understanding

Although Multimodal Large Language Models (MLLMs) have advanced rapidly, they still face notable cha...

Thinking Like a Botanist: Challenging Multimodal Language Models with Intent-Driven Chain-of-Inquiry

Vision evaluations are typically done through multi-step processes. In most contemporary fields, exp...

Hallucination Early Detection in Diffusion Models

Text-to-Image generation has seen significant advancements in output realism with the advent of diff...

Improving clinical interpretability of linear neuroimaging models through feature whitening

Linear models are widely used in computational neuroimaging to identify biomarkers associated with b...

R-CoV: Region-Aware Chain-of-Verification for Alleviating Object Hallucinations in LVLMs

Large vision-language models (LVLMs) have demonstrated impressive performance in various multimodal ...

Detecting Hallucinations in SpeechLLMs at Inference Time Using Attention Maps

Hallucinations in Speech Large Language Models (SpeechLLMs) pose significant risks, yet existing det...

Lucky High Dynamic Range Smartphone Imaging

While the human eye can perceive an impressive twenty stops of dynamic range, smartphone camera sens...

Optimally Bridging Semantics and Data: Generative Semantic Communication via Schrödinger Bridge

Generative Semantic Communication (GSC) is a promising solution for image transmission over narrow-b...

Region-Grounded Report Generation for 3D Medical Imaging: A Fine-Grained Dataset and Graph-Enhanced Framework

Automated medical report generation for 3D PET/CT imaging is fundamentally challenged by the high-di...

When Text Hijacks Vision: Benchmarking and Mitigating Text Overlay-Induced Hallucination in Vision Language Models

Recent advances in Vision-Language Models (VLMs) have substantially enhanced their ability across mu...

Aligning What Vision-Language Models See and Perceive with Adaptive Information Flow

Vision-Language Models (VLMs) have demonstrated strong capability in a wide range of tasks such as v...

MetaMuse: A Multi-Agent AI System for Biomedical Metadata Curation and Harmonization

Inconsistent and unstructured metadata in public biomedical repositories, such as the Gene Expressio...

Multi-Task LLM with LoRA Fine-Tuning for Automated Cancer Staging and Biomarker Extraction

Pathology reports serve as the definitive record for breast cancer staging, yet their unstructured f...

Domain-Specific Latent Representations Improve the Fidelity of Diffusion-Based Medical Image Super-Resolution

Latent diffusion models for medical image super-resolution universally inherit variational autoencod...

Decoding by Perturbation: Mitigating MLLM Hallucinations via Dynamic Textual Perturbation

Multimodal Large Language Models frequently suffer from inference hallucinations, partially stemming...

T2I-BiasBench: A Multi-Metric Framework for Auditing Demographic and Cultural Bias in Text-to-Image Models

Text-to-image (T2I) generative models achieve impressive visual fidelity but inherit and amplify dem...

SceneCritic: A Symbolic Evaluator for 3D Indoor Scene Synthesis

Large Language Models (LLMs) and Vision-Language Models (VLMs) increasingly generate indoor scenes t...

LogitDynamics: Reliable ViT Error Detection from Layerwise Logit Trajectories

Reliable confidence estimation is critical when deploying vision models. We study error prediction: ...

MedVR: Annotation-Free Medical Visual Reasoning via Agentic Reinforcement Learning

Medical Vision-Language Models (VLMs) hold immense promise for complex clinical tasks, but their rea...

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