Erfan Ghadery


2021

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LIIR at SemEval-2021 task 6: Detection of Persuasion Techniques In Texts and Images using CLIP features
Erfan Ghadery | Damien Sileo | Marie-Francine Moens
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)

We describe our approach for SemEval-2021 task 6 on detection of persuasion techniques in multimodal content (memes). Our system combines pretrained multimodal models (CLIP) and chained classifiers. Also, we propose to enrich the data by a data augmentation technique. Our submission achieves a rank of 8/16 in terms of F1-micro and 9/16 with F1-macro on the test set.

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Just Ask! Evaluating Machine Translation by Asking and Answering Questions
Mateusz Krubiński | Erfan Ghadery | Marie-Francine Moens | Pavel Pecina
Proceedings of the Sixth Conference on Machine Translation

In this paper, we show that automatically-generated questions and answers can be used to evaluate the quality of Machine Translation (MT) systems. Building on recent work on the evaluation of abstractive text summarization, we propose a new metric for system-level MT evaluation, compare it with other state-of-the-art solutions, and show its robustness by conducting experiments for various MT directions.

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MTEQA at WMT21 Metrics Shared Task
Mateusz Krubiński | Erfan Ghadery | Marie-Francine Moens | Pavel Pecina
Proceedings of the Sixth Conference on Machine Translation

In this paper, we describe our submission to the WMT 2021 Metrics Shared Task. We use the automatically-generated questions and answers to evaluate the quality of Machine Translation (MT) systems. Our submission builds upon the recently proposed MTEQA framework. Experiments on WMT20 evaluation datasets show that at the system-level the MTEQA metric achieves performance comparable with other state-of-the-art solutions, while considering only a certain amount of information from the whole translation.

2020

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LIIR at SemEval-2020 Task 12: A Cross-Lingual Augmentation Approach for Multilingual Offensive Language Identification
Erfan Ghadery | Marie-Francine Moens
Proceedings of the Fourteenth Workshop on Semantic Evaluation

This paper presents our system entitled ‘LIIR’ for SemEval-2020 Task 12 on Multilingual Offensive Language Identification in Social Media (OffensEval 2). We have participated in sub-task A for English, Danish, Greek, Arabic, and Turkish languages. We adapt and fine-tune the BERT and Multilingual Bert models made available by Google AI for English and non-English languages respectively. For the English language, we use a combination of two fine-tuned BERT models. For other languages we propose a cross-lingual augmentation approach in order to enrich training data and we use Multilingual BERT to obtain sentence representations.