Papers with textual entailment problem
A weakly supervised textual entailment approach to zero-shot text classification (2023.eacl-main)
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Marc Pàmies, Joan Llop, Francesco Multari, Nicolau Duran-Silva, César Parra-Rojas, Aitor Gonzalez-Agirre, Francesco Alessandro Massucci, Marta Villegas
| Challenge: | Existing methods to train on weakly supervised datasets are expensive due to the computational cost of pre-training. |
| Approach: | They propose a method that trains on a weakly supervised dataset that is used as a proxy for a textual entailment problem and a target zero-shot text classification task. |
| Outcome: | The proposed model achieves state-of-the-art performance in the scientific domain and competitive results in other areas. |
Not all quantifiers are equal: Probing Transformer-based language models’ understanding of generalised quantifiers (2023.emnlp-main)
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| Challenge: | Recent popularity of generalised quantifiers and role in linguistics and logic raises the question of how they affect transformer-based language models (TLMs) |
| Approach: | They propose to use textual entailment to assess the ability of TLMs to learn the meanings of generalised quantifiers by using a textual model-checking problem defined in a purely logical sense. |
| Outcome: | The proposed method allows the automatic construction of datasets with respect to which we can assess the ability of TLMs to learn the meanings of generalised quantifiers. |
Uncovering Agendas: A Novel French & English Dataset for Agenda Detection on Social Media (2024.lrec-main)
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| Challenge: | a social media analysis of online influence campaigns can reveal the sources of agenda setting . annotated data is limited or nonexistent, but there are methods to detect agenda control . |
| Approach: | They propose a method for detecting instances of agenda control through social media . they use a modest corpus of tweets centered on the 2022 french presidential election . |
| Outcome: | The proposed method overcomes the requirement for large annotated training dataset. |