Papers by Gaël Dias
Analyzing Symptom-based Depression Level Estimation through the Prism of Psychiatric Expertise (2024.lrec-main)
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| Challenge: | Existing approaches to automate depression estimation ignore medical professionals' knowledge of the problem. |
| Approach: | They propose to integrate domain experts' knowledge into a DAIC-WOZ dataset and propose a transformer-based model that incorporates their annotations. |
| Outcome: | The proposed model shows a strong correlation between the psychological tendencies of medical professionals and the behavior of the proposed model. |
Understanding Feature Focus in Multitask Settings for Lexico-semantic Relation Identification (2021.findings-acl)
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| Challenge: | Lexico-semantic relations embody symmetric and asymmetric linguistic phenomena such as synonymy (e.g. phone telephone), cohyponymy (, cohypoonymy, hypernymy, meronymy) and more can be enumerated. |
| Approach: | They propose to combine feature engineering and multitask architectures to identify lexico-semantic relations by combining asymmetric distributional features with shared-private models. |
| Outcome: | The proposed models improve over binary and fully-shared classifiers and balance the focus on features between private and shared layers 1 and 2 . |
Discourse Realization of Generics in Human and LLM-generated Texts (2026.acl-long)
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| Challenge: | Large Language Models produce texts that appear coherent and credible, even when their factual reliability is uncertain. |
| Approach: | They propose a text-level genericity score derived from clause-level annotations and apply it to argumentative essays produced by humans and LLMs. |
| Outcome: | The proposed model is less generic than LLM-produced arguments, the study shows . higher genericity correlates with less structured, paratactic structures, the research shows a. |
Transfer Learning for Humor Detection by Twin Masked Yellow Muppets (2022.aacl-short)
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| Challenge: | Existing humor classification systems have been dealing with different forms of humor independently. |
| Approach: | They propose to combine different forms of humor to tackle different humor types by a shared-private multitask architecture using a transfer learning paradigm. |
| Outcome: | The proposed architecture shows statistically significant improvements over baselines and accounting for new state-of-the-art figures for two datasets. |
Facilitating Cognitive Accessibility with LLMs: A Multi-Task Approach to Easy-to-Read Text Generation (2025.emnlp-main)
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| Challenge: | Existing approaches to make complex texts more accessible for people with cognitive impairments are time-consuming and resource-intensive. |
| Approach: | They propose a multi-task learning approach that trains models jointly on text summarization, text simplification, and ETR generation. |
| Outcome: | The proposed approach outperforms other approaches in in-domain settings while achieving better generalization in out-of-domain scenarios. |
Par-ITA: Benchmarking Seq2Seq and LLMs on a Human-Supervised Parallel Corpus for Italian Hyperpartisan Neutralization (2026.acl-long)
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| Challenge: | a new study examines the role of hyperpartisan content in online polarization in the social web. |
| Approach: | They propose a human-supervised parallel corpus for italian hyperpartisan neutralization of 2,475 paragraph pairs. |
| Outcome: | The proposed dataset is the first human-supervised parallel corpus for italian hyperpartisan neutralization of 2,475 paragraph pairs. |