1 citations · 4 across the 20 of their papers we have counts for
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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…
Emo3D: Metric and Benchmarking Dataset for 3D Facial Expression Generation from Emotion Description
Mahshid Dehghani, Amirahmad Shafiee, Ali Shafiei +6
Existing 3D facial emotion modeling have been constrained by limited emotion classes and insufficient datasets. This paper introduces "Emo3D", an extensive "Text-Image-Expression d…
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…
MFace: A Unified Multi-Modal Multilingual Framework for Human Face Generation and Editing
Mohammadreza Mofayezi, Reza Alipour, Mohammad Ali Kakavand +1
Human face generation and editing represent an essential task in the era of computer vision and the digital world. Recent studies have shown remarkable progress in multi-modal face…