1 citations · 4 across the 20 of their papers we have counts for
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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…
QuranicMMLU: A Cognitively-Aware Benchmark for Evaluating Generative AI Solutions on Quranic Linguistic Knowledge
Rawan El Ghali, Umm Kulsoom, Anas Madkoor +10
We introduce QuranicMMLU, a benchmark for evaluating generative AI on Quranic Arabic across multiple dimensions of linguistic complexity. Existing Quranic benchmarks center on gene…
Fanar 2.0: Arabic Generative AI Stack
FANAR TEAM, Ummar Abbas, Mohammad Shahmeer Ahmad +34
We present Fanar 2.0, the second generation of Qatar's Arabic-centric Generative AI platform. Sovereignty is a first-class design principle: every component, from data pipelines to…
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…
The Alignment Veto: How Safety Training Suppresses Cultural Knowledge in LLMs
Pardis Sadat Zahraei, Gokhan Tur, Dilek Hakkani-Tür +1
What happens inside a language model when alignment training conflicts with a cultural value it encodes? Across 16 MENA countries, 26 models, and 1.53M human survey responses, we s…
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…
EiCAP: Beyond Fluency, Probing and Improving Emotional Intelligence in LLMs via Psychologically Grounded Multi-Turn Dialogue
Nizi Nazar, Pardis Sadat Zahraei, Dilek Hakkani-Tür +2
Large Language Models increasingly serve in emotionally sensitive roles, including mental health support, education, and crisis response, yet they lack a principled framework for a…
ParsiPy: NLP Toolkit for Historical Persian Texts in Python
Farhan Farsi, Parnian Fazel, Sepand Haghighi +5
The study of historical languages presents unique challenges due to their complex orthographic systems, fragmentary textual evidence, and the absence of standardized digital repres…
MorphBPE: A Morpho-Aware Tokenizer Bridging Linguistic Complexity for Efficient LLM Training Across Morphologies
Ehsaneddin Asgari, Yassine El Kheir, Mohammad Ali Sadraei Javaheri
Tokenization is fundamental to Natural Language Processing (NLP), directly impacting model efficiency and linguistic fidelity. While Byte Pair Encoding (BPE) is widely used in Larg…
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…
AIMA at SemEval-2024 Task 3: Simple Yet Powerful Emotion Cause Pair Analysis
Alireza Ghahramani Kure, Mahshid Dehghani, Mohammad Mahdi Abootorabi +3
The SemEval-2024 Task 3 presents two subtasks focusing on emotion-cause pair extraction within conversational contexts. Subtask 1 revolves around the extraction of textual emotion-…
AIMA at SemEval-2024 Task 10: History-Based Emotion Recognition in Hindi-English Code-Mixed Conversations
Mohammad Mahdi Abootorabi, Nona Ghazizadeh, Seyed Arshan Dalili +3
In this study, we introduce a solution to the SemEval 2024 Task 10 on subtask 1, dedicated to Emotion Recognition in Conversation (ERC) in code-mixed Hindi-English conversations. E…
CLASP: Contrastive Language-Speech Pretraining for Multilingual Multimodal Information Retrieval
Mohammad Mahdi Abootorabi, Ehsaneddin Asgari
This study introduces CLASP (Contrastive Language-Speech Pretraining), a multilingual, multimodal representation tailored for audio-text information retrieval. CLASP leverages the…
TuringQ: Benchmarking AI Comprehension in Theory of Computation
Pardis Sadat Zahraei, Ehsaneddin Asgari
We present TuringQ, the first benchmark designed to evaluate the reasoning capabilities of large language models (LLMs) in the theory of computation. TuringQ consists of 4,006 unde…
SuperPos-Prompt: Enhancing Soft Prompt Tuning of Language Models with Superposition of Multi Token Embeddings
MohammadAli SadraeiJavaeri, Ehsaneddin Asgari, Alice Carolyn McHardy +1
Soft prompt tuning techniques have recently gained traction as an effective strategy for the parameter-efficient tuning of pretrained language models, particularly minimizing the r…
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…
KhabarChin: Automatic Detection of Important News in the Persian Language
Hamed Hematian Hemati, Arash Lagzian, Moein Salimi Sartakhti +2
Being aware of important news is crucial for staying informed and making well-informed decisions efficiently. Natural Language Processing (NLP) approaches can significantly automat…