8 papers
A Unified Evaluation Framework for Trustworthy Large Language Models, Agentic AI, and Multimodal Systems
Shaina Raza, Ahmed Y. Radwan, Imran Liaquat +1
Benchmark scores alone provide an incomplete basis for assessing the trustworthiness of modern artificial intelligence systems. Large language models (LLMs), agentic systems, and m…
Stress-Testing Efficient Responsible-AI Evaluation: When Compute Savings Change Benchmark Conclusions
Ahmed El Kady, Aravind Narayanan, Rehana Riaz +2
Efficient evaluation changes the protocol used to support claims about model behavior, yet it is rarely tested whether those claims remain stable after the evaluation itself is mad…
SONIC-O1: A Real-World Benchmark for Evaluating Multimodal Large Language Models on Audio-Video Understanding
Ahmed Y. Radwan, Christos Emmanouilidis, Hina Tabassum +2
Multimodal Large Language Models (MLLMs) are a major focus of recent AI research. However, most prior work focuses on static image understanding, while their ability to process seq…
Position: Sustainable Open-Source AI Requires Tracking the Cumulative Footprint of Derivatives
Shaina Raza, Iuliia Zarubiieva, Ahmed Y. Radwan +4
Open-source AI is scaling rapidly, and model hubs now host millions of artifacts. Each foundation model can spawn large numbers of fine-tunes, adapters, quantizations, merges, and…
Reducing Hallucinations in LLMs via Factuality-Aware Preference Learning
Sindhuja Chaduvula, Ahmed Y. Radwan, Azib Farooq +2
Preference alignment methods such as RLHF and Direct Preference Optimization (DPO) improve instruction following, but they can also reinforce hallucinations when preference judgmen…
Just as Humans Need Vaccines, So Do Models: Model Immunization to Combat Falsehoods
Shaina Raza, Rizwan Qureshi, Azib Farooq +4
Large language models (LLMs) reproduce misinformation not by memorizing false facts alone, but by learning the linguistic patterns that make falsehoods persuasive, such as hedging,…
Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights
Tahniat Khan, Soroor Motie, Sedef Akinli Kocak +1
The rapid adoption of large language models (LLMs) has led to significant energy consumption and carbon emissions, posing a critical challenge to the sustainability of generative A…
FairSense-AI: Responsible AI Meets Sustainability
Shaina Raza, Mukund Sayeeganesh Chettiar, Matin Yousefabadi +2
In this paper, we introduce FairSense-AI: a multimodal framework designed to detect and mitigate bias in both text and images. By leveraging Large Language Models (LLMs) and Vision…