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Tamer Elsayed

5 accepted papers

2025

TRATES: Trait-Specific Rubric-Assisted Cross-Prompt Essay Scoring

ACL 2025finding

Research on holistic Automated Essay Scoring (AES) is long-dated; yet, there is a notable lack of attention for assessing essays according to individual traits. In this work, we propose TRATES, a novel trait-specific and rubric-based cross-prompt AES framework that is generic yet specific to the und…

2024

Can Large Language Models Automatically Score Proficiency of Written Essays?

COLING 2024main

Although several methods were proposed to address the problem of automated essay scoring (AES) in the last 50 years, there is still much to desire in terms of effectiveness. Large Language Models (LLMs) are transformer-based models that demonstrate extraordinary capabilities on various tasks. In thi…

2023

IDRISI-RA: The First Arabic Location Mention Recognition Dataset of Disaster Tweets

ACL 2023long

Extracting geolocation information from social media data enables effective disaster management, as it helps response authorities; for example, in locating incidents for planning rescue activities, and affected people for evacuation. Nevertheless, geolocation extraction is greatly understudied for t…

2021

Automated Fact-Checking for Assisting Human Fact-Checkers

IJCAI 2021poster

The reporting and the analysis of current events around the globe has expanded from professional, editor-lead journalism all the way to citizen journalism. Nowadays, politicians and other key players enjoy direct access to their audiences through social media, bypassing the filters of official cable…

Cited by 281SourcePDFScholar
2020

Are We Ready for this Disaster? Towards Location Mention Recognition from Crisis Tweets

COLING 2020main

The widespread usage of Twitter during emergencies has provided a new opportunity and timely resource to crisis responders for various disaster management tasks. Geolocation information of pertinent tweets is crucial for gaining situational awareness and delivering aid. However, the majority of twee…

Cited by 16SourcePDFScholar