Papers by Chadi Helwe
TINA: Textual Inference with Negation Augmentation (2022.findings-emnlp)
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| Challenge: | Existing transformer-based models perform poorly on textual entailment when examples contain negations. |
| Approach: | They propose a new definition of textual entailment that captures negation and a principled technique for negated data augmentation that can be combined with unlikelihood loss function. |
| Outcome: | The proposed method significantly improves on textual entailment datasets with negations without sacrificing performance on datasets without negation. |
Navigating the Political Compass: Evaluating Multilingual LLMs across Languages and Nationalities (2025.findings-acl)
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| Challenge: | Large Language Models (LLMs) are ubiquitous in today’s technological landscape, boasting a plethora of applications, and even endangering human jobs in complex and creative fields. |
| Approach: | They evaluate the political bias of 15 multilingual LLMs using the Political Compass Test and assign a nationality to each model. |
| Outcome: | The models on the 50 most populous countries and their official languages exhibit political bias. |
MAFALDA: A Benchmark and Comprehensive Study of Fallacy Detection and Classification (2024.naacl-long)
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| Challenge: | Fallacy classification is a task of broad importance due to advances in deep learning and availability of more data. |
| Approach: | They propose a new annotation scheme tailored for subjective NLP tasks and a method designed to handle subjectivity. |
| Outcome: | The proposed approach integrates existing fallacy classification datasets with new ones. |
LogiTorch: A PyTorch-based library for logical reasoning on natural language (2022.emnlp-demos)
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| Challenge: | Logical reasoning on natural language is one of the most challenging tasks for deep learning models. |
| Approach: | They propose a library that includes logical reasoning benchmarks and models . they use a dataset to run the library or fine tune the models with different hyperparameters . |
| Outcome: | This library includes logical reasoning benchmarks, models, utility functions and co-reference resolution. |