5 papers
Neural at ArchEHR-QA 2026: One Method Fits All: Unified Prompt Optimization for Clinical QA over EHRs
Abrar Majeedi, Viswanatha Reddy Gajjala, Sai Prasanna Teja Reddy Bogireddy +1
Automated question answering (QA) over electronic health records (EHRs) demands precise evidence retrieval, faithful answer generation, and explicit grounding of answers in clinica…
DUALVISION: RGB-Infrared Multimodal Large Language Models for Robust Visual Reasoning
Abrar Majeedi, Zhiyuan Ruan, Ziyi Zhao +3
Multimodal large language models (MLLMs) have achieved impressive performance on visual perception and reasoning tasks with RGB imagery, yet they remain fragile under common degrad…
Restore-R1: Efficient Image Restoration Agents via Reinforcement Learning with Multimodal LLM Perceptual Feedback
Jianglin Lu, Yuanwei Wu, Ziyi Zhao +4
Complex image restoration aims to recover high-quality images from inputs affected by multiple degradations such as blur, noise, rain, and compression artifacts. Recent restoration…
Neural at ArchEHR-QA 2025: Agentic Prompt Optimization for Evidence-Grounded Clinical Question Answering
Sai Prasanna Teja Reddy Bogireddy, Abrar Majeedi, Viswanatha Reddy Gajjala +3
Automated question answering (QA) over electronic health records (EHRs) can bridge critical information gaps for clinicians and patients, yet it demands both precise evidence retri…
LETS Forecast: Learning Embedology for Time Series Forecasting
Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV +2
Real-world time series are often governed by complex nonlinear dynamics. Understanding these underlying dynamics is crucial for precise future prediction. While deep learning has a…