6 papers
Adaptive Ecological Momentary Assessment with a Hybrid Language Model: Formative Expert Review and Retrospective Evaluation
Arash Ahmadi, Dingjing Shi, Yaser M. Banad
Ecological momentary assessment (EMA) measures experience in daily life, but fixed questionnaires and schedules collect information of uneven value and can interrupt participants.…
Improving Heart-Focused Medical Question Answering in LLMs via Variance-Aware Rubric Rewards with GRPO
Arash Ahmadi, Parisa Masnadi Khiabani, Sarah Sharif +3
Large Language Models (LLMs) have shown strong promise in healthcare applications. Yet deploying general-purpose models in real-world settings remains difficult due to data privacy…
Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning
Arash Ahmadi, Sarah Sharif, Yaser +1
Mathematical reasoning is a key benchmark for large language models. Reinforcement learning is a standard post-training mechanism for improving the reasoning capabilities of large…
Improving Aviation Safety Analysis: Automated HFACS Classification Using Reinforcement Learning with Group Relative Policy Optimization
Arash Ahmadi, Sarah Sharif, Yaser Banad
Analyzing the human factors behind aviation accidents is crucial for preventing future incidents, yet traditional methods using the Human Factors Analysis and Classification System…
MCP Bridge: A Lightweight, LLM-Agnostic RESTful Proxy for Model Context Protocol Servers
Arash Ahmadi, Sarah Sharif, Yaser M. Banad
Large Language Models (LLMs) are increasingly augmented with external tools through standardized interfaces like the Model Context Protocol (MCP). However, current MCP implementati…
A Comparative Study of Sampling Methods with Cross-Validation in the FedHome Framework
Arash Ahmadi, Sarah S. Sharif, Yaser M. Banad
This paper presents a comparative study of sampling methods within the FedHome framework, designed for personalized in-home health monitoring. FedHome leverages federated learning…