most citedLXMERT Model Compression for Visual Question Answering

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024

FarExStance: Explainable Stance Detection for Farsi

Majid Zarharan, Maryam Hashemi, Malika Behroozrazegh +3

We introduce FarExStance, a new dataset for explainable stance detection in Farsi. Each instance in this dataset contains a claim, the stance of an article or social media post tow…

cs.CV2024

Illusory VQA: Benchmarking and Enhancing Multimodal Models on Visual Illusions

Mohammadmostafa Rostamkhani, Baktash Ansari, Hoorieh Sabzevari +2

In recent years, Visual Question Answering (VQA) has made significant strides, particularly with the advent of multimodal models that integrate vision and language understanding. H…

cs.CL2024

eagerlearners at SemEval2024 Task 5: The Legal Argument Reasoning Task in Civil Procedure

Hoorieh Sabzevari, Mohammadmostafa Rostamkhani, Sauleh Eetemadi

This study investigates the performance of the zero-shot method in classifying data using three large language models, alongside two models with large input token sizes and the two…

cs.CL2024

BAMO at SemEval-2024 Task 9: BRAINTEASER: A Novel Task Defying Common Sense

Baktash Ansari, Mohammadmostafa Rostamkhani, Sauleh Eetemadi

This paper outlines our approach to SemEval 2024 Task 9, BRAINTEASER: A Novel Task Defying Common Sense. The task aims to evaluate the ability of language models to think creativel…

cs.CV20231 cited

LXMERT Model Compression for Visual Question Answering

Maryam Hashemi, Ghazaleh Mahmoudi, Sara Kodeiri +2

Large-scale pretrained models such as LXMERT are becoming popular for learning cross-modal representations on text-image pairs for vision-language tasks. According to the lottery t…