22 citations · 25 across the 10 of their papers we have counts for
7 papers · 1 filter
Almieyar: A Culturally Grounded Benchmark for Multi-Dialect Arabic Speech Recognition
Omid Ghahroodi, Anas Madkoor, Dima Faris Al Saudi +37
Arabic speech technology has largely focused on Modern Standard Arabic, leaving the living dialects spoken by hundreds of millions under-served. We introduce ALMIEYAR, a culturally…
The Judge Who Never Admits: Hidden Shortcuts in LLM-based Evaluation
Arash Marioriyad, Omid Ghahroodi, Ehsaneddin Asgari +2
Large language models (LLMs) are increasingly used as automatic judges to evaluate system outputs in tasks such as reasoning, question answering, and creative writing. A faithful j…
ADAM: A Diverse Archive of Mankind for Evaluating and Enhancing LLMs in Biographical Reasoning
Jasin Cekinmez, Omid Ghahroodi, Saad Fowad Chandle +2
We introduce ADAM (A Diverse Archive of Mankind), a framework for evaluating and improving multimodal large language models (MLLMs) in biographical reasoning. To the best of our kn…
ELAB: Extensive LLM Alignment Benchmark in Persian Language
Zahra Pourbahman, Fatemeh Rajabi, Mohammadhossein Sadeghi +5
This paper presents a comprehensive evaluation framework for aligning Persian Large Language Models (LLMs) with critical ethical dimensions, including safety, fairness, and social…
Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation
Mohammad Mahdi Abootorabi, Amirhosein Zobeiri, Mahdi Dehghani +5
Large Language Models (LLMs) suffer from hallucinations and outdated knowledge due to their reliance on static training data. Retrieval-Augmented Generation (RAG) mitigates these i…
Khayyam Challenge (PersianMMLU): Is Your LLM Truly Wise to The Persian Language?
Omid Ghahroodi, Marzia Nouri, Mohammad Vali Sanian +5
Evaluating Large Language Models (LLMs) is challenging due to their generative nature, necessitating precise evaluation methodologies. Additionally, non-English LLM evaluation lags…
The Touché23-ValueEval Dataset for Identifying Human Values behind Arguments
Nailia Mirzakhmedova, Johannes Kiesel, Milad Alshomary +11
We present the Touché23-ValueEval Dataset for Identifying Human Values behind Arguments. To investigate approaches for the automated detection of human values behind arguments, we…