6 papers
Toward Trustworthy Large Language Model Agents in Healthcare
Hadi Hasan, Safaa Salman, Adam Tai Abou Dargham +2
Healthcare appointment scheduling remains a persistent operational bottleneck, driven by manual coordination, fragmented legacy systems, and high administrative overhead. These ine…
QuanBench+: A Unified Multi-Framework Benchmark for LLM-Based Quantum Code Generation
Ali Slim, Haydar Hamieh, Jawad Kotaich +5
Large Language Models (LLMs) are increasingly used for code generation, yet quantum code generation is still evaluated mostly within single frameworks, making it difficult to separ…
TAPS: Task Aware Proposal Distributions for Speculative Sampling
Mohamad Zbib, Mohamad Bazzi, Ammar Mohanna +2
Speculative decoding accelerates autoregressive generation by letting a lightweight draft model propose future tokens that a larger target model then verifies in parallel. In pract…
AraLingBench A Human-Annotated Benchmark for Evaluating Arabic Linguistic Capabilities of Large Language Models
Mohammad Zbeeb, Hasan Abed Al Kader Hammoud, Sina Mukalled +5
We present AraLingBench: a fully human annotated benchmark for evaluating the Arabic linguistic competence of large language models (LLMs). The benchmark spans five core categories…
Chained Prompting for Better Systematic Review Search Strategies
Fatima Nasser, Fouad Trad, Ammar Mohanna +2
Systematic reviews require the use of rigorously designed search strategies to ensure both comprehensive retrieval and minimization of bias. Conventional manual approaches, althoug…
Optimizing Deep Neural Networks using Safety-Guided Self Compression
Mohammad Zbeeb, Mariam Salman, Mohammad Bazzi +1
The deployment of deep neural networks on resource-constrained devices necessitates effective model com- pression strategies that judiciously balance the reduction of model size wi…