Papers by Elham Mohammadi
Cooking Up a Neural-based Model for Recipe Classification (2020.lrec-1)
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Elham Mohammadi, Nada Naji, Louis Marceau, Marc Queudot, Eric Charton, Leila Kosseim, Marie-Jean Meurs
| Challenge: | a dataset of cooking recipes in French is highly imbalanced due to collaborative nature of the dataset . authors propose a neural-based model to address the first task of the DEFT 2013 shared task . |
| Approach: | They propose a neural-based model to address the first task of the DEFT 2013 shared task . they use state-of-the-art embedding approaches and deep architectures to address imbalanced dataset . |
| Outcome: | The proposed model outperforms models that use only pretrained embeddings in micro and macro F1 scores. |
On the Creation of a Corpus for Coherence Evaluation of Discursive Units (2020.lrec-1)
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| Challenge: | Most corpora for textual coherence evaluation are composed of randomly shuffled sentences that focus on sentence ordering. |
| Approach: | They propose to use a variety of corruption strategies to build a corpus of incoherent pairs of sentences by swapping their discourse connective or a discourse argument. |
| Outcome: | The proposed corpus is constructed from discourse argument pairs from the Penn Discourse Tree Bank and is compared with existing corpus models. |
LLM Evaluate: An Industry-Focused Evaluation Tool for Large Language Models (2025.coling-industry)
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| Challenge: | Large Language Models (LLMs) have demonstrated impressive capability to solve a wide range of tasks in recent years. |
| Approach: | They propose to build an on-premise system for LLM evaluation to address the challenges in the evaluation of LLMs in real-world industrial settings. |
| Outcome: | The proposed evaluation system protects customer privacy and protects data integrity in real-world industrial environments. |