1 citations · 4 across the 20 of their papers we have counts for
4 papers · 2 filters
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…