Zobrazeno 1 - 10
of 89
pro vyhledávání: '"Abdallah Abdelrahman"'
Detecting and answering ambiguous questions has been a challenging task in open-domain question answering. Ambiguous questions have different answers depending on their interpretation and can take diverse forms. Temporally ambiguous questions are one
Externí odkaz:
http://arxiv.org/abs/2409.17046
Automatic Question Answering (QA) systems rely on contextual information to provide accurate answers. Commonly, contexts are prepared through either retrieval-based or generation-based methods. The former involves retrieving relevant documents from a
Externí odkaz:
http://arxiv.org/abs/2409.16096
We introduce ComplexTempQA, a large-scale dataset consisting of over 100 million question-answer pairs designed to tackle the challenges in temporal question answering. ComplexTempQA significantly surpasses existing benchmarks like HOTPOTQA, TORQUE,
Externí odkaz:
http://arxiv.org/abs/2406.04866
Autor:
Abdallah, Abdelrahman, Abdalla, Mahmoud, Kasem, Mahmoud SalahEldin, Mahmoud, Mohamed, Abdelhalim, Ibrahim, Elkasaby, Mohamed, ElBendary, Yasser, Jatowt, Adam
In the fields of Optical Character Recognition (OCR) and Natural Language Processing (NLP), integrating multilingual capabilities remains a critical challenge, especially when considering languages with complex scripts such as Arabic. This paper intr
Externí odkaz:
http://arxiv.org/abs/2406.04493
Autor:
Abdallah, Abdelrahman, Kasem, Mahmoud, Abdalla, Mahmoud, Mahmoud, Mohamed, Elkasaby, Mohamed, Elbendary, Yasser, Jatowt, Adam
In this paper, we address the significant gap in Arabic natural language processing (NLP) resources by introducing ArabicaQA, the first large-scale dataset for machine reading comprehension and open-domain question answering in Arabic. This comprehen
Externí odkaz:
http://arxiv.org/abs/2403.17848
This paper presents a comprehensive survey of research works on the topic of form understanding in the context of scanned documents. We delve into recent advancements and breakthroughs in the field, highlighting the significance of language models an
Externí odkaz:
http://arxiv.org/abs/2403.04080
The extraction of key information from receipts is a complex task that involves the recognition and extraction of text from scanned receipts. This process is crucial as it enables the retrieval of essential content and organizing it into structured d
Externí odkaz:
http://arxiv.org/abs/2309.09800
Autor:
Abdallah, Abdelrahman, Jatowt, Adam
Open-domain question answering (QA) tasks usually require the retrieval of relevant information from a large corpus to generate accurate answers. We propose a novel approach called Generator-Retriever-Generator (GRG) that combines document retrieval
Externí odkaz:
http://arxiv.org/abs/2307.11278
Publikováno v:
J Big Data 10, 127 (2023)
Answering questions related to the legal domain is a complex task, primarily due to the intricate nature and diverse range of legal document systems. Providing an accurate answer to a legal query typically necessitates specialized knowledge in the re
Externí odkaz:
http://arxiv.org/abs/2304.06623
Autor:
Amany Omar Mohamed Omar, Yousef Ahmed Yousef Ahmed, Abd-Elazim Ahmed Abo Elfadl, Abeer Houssein Ali, Amal Abdallah Abdelrahman, Khaled Mohamed Khaled Ali
Publikováno v:
The Egyptian Journal of Bronchology, Vol 18, Iss 1, Pp 1-8 (2024)
Abstract Background Acute pulmonary embolism (APE) is a serious illness. Identifying prognostic factors for APE may help in the management of those patients. This study’s objective was to evaluate the prognostic value of laboratory markers in predi
Externí odkaz:
https://doaj.org/article/909c2463d4534375bcb0ed959a57bd6d