Papers by Lauriane Aufrant
Is NLP Ready for Standardization? (2022.findings-emnlp)
Copied to clipboard
| Challenge: | a number of scientific fields, including telecommunications, networks and multimedia, lack standards in the field of NLP. |
| Approach: | They propose to examine how NLP lacks standards and how that can impact society, industry and regulations. |
| Outcome: | The proposed standards examine the needs of NLP researchers and industry . they argue that the lack of standards can impact the field, society and industry. |
UkraiNER: A New Corpus and Annotation Scheme towards Comprehensive Entity Recognition (2024.lrec-main)
Copied to clipboard
| Challenge: | Named entity recognition excludes nested, discontinuous, non-named entities in practice . despite attempts to broaden their coverage, the most restrictive variant of NER remains the default . |
| Approach: | They propose a new annotation scheme that offers higher comprehensiveness while preserving simplicity. |
| Outcome: | The proposed scheme offers higher comprehensiveness while preserving simplicity . it also includes an annotation tool to implement the scheme on the corpus UkraiNER . |
Exploiting Dynamic Oracles to Train Projective Dependency Parsers on Non-Projective Trees (N18-2)
Copied to clipboard
| Challenge: | Several strategies have been proposed to overcome the projectivity constraint by introducing transition-based dependency parsers that can build non-projective dependencies. |
| Approach: | They propose a modification of dynamic oracles to allow use of non-projective data . their method consistently outperforms traditional projectivization and pseudo-projectivisation approaches . |
| Outcome: | The proposed method outperforms projectivization and pseudo-projectivisation methods on 73 treebanks and achieves significant gains for non-projective languages. |
Quantifying training challenges of dependency parsers (C18-1)
Copied to clipboard
| Challenge: | a new metric is introduced to evaluate the difficulty to learn a given class of dependencies . a series of systematic computations using that metric have revealed interesting properties of the 3 considered parsing algorithms . |
| Approach: | They introduce a new metric to evaluate the difficulty to learn a given class of dependencies . they use it to characterize the information conveyed by cross-lingual parsers . |
| Outcome: | The proposed metric reveals the kind of dependencies that require high effort during training . it also shows that cross-lingual parsers can provide better quality information . |