Statements (81)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Performance_Monitoring
|
| gptkbp:aims_to_improve |
model performance
|
| gptkbp:available_at |
gptkb:Git_Hub
|
| gptkbp:collaborated_with |
open-source projects
research initiatives tech companies |
| gptkbp:contains |
English questions
non-English questions |
| gptkbp:designed_for |
question answering
|
| gptkbp:developed_by |
gptkb:Google_Research
community feedback collaborative efforts |
| gptkbp:evaluates |
language models
|
| gptkbp:facilitates |
evaluation of QA systems
|
| gptkbp:focuses_on |
cross-lingual question answering
|
| https://www.w3.org/2000/01/rdf-schema#label |
XQu AD
|
| gptkbp:includes |
multiple languages
|
| gptkbp:is_adopted_by |
industry practitioners
|
| gptkbp:is_analyzed_in |
performance metrics
studies bias detection |
| gptkbp:is_based_on |
gptkb:Transformers
|
| gptkbp:is_cited_in |
academic papers
|
| gptkbp:is_compatible_with |
gptkb:Tensor_Flow
gptkb:Py_Torch |
| gptkbp:is_designed_to |
assess multilingual capabilities
|
| gptkbp:is_documented_in |
research papers
research institutions technical reports |
| gptkbp:is_evaluated_by |
automated systems
accuracy robustness peer reviews user studies human annotators standard metrics |
| gptkbp:is_explored_in |
workshops and seminars
research collaborations thesis work |
| gptkbp:is_influenced_by |
previous benchmarks
|
| gptkbp:is_integrated_with |
QA systems
|
| gptkbp:is_part_of |
gptkb:AI_technology
evaluation frameworks NLP tasks |
| gptkbp:is_promoted_by |
conferences
online platforms |
| gptkbp:is_promoted_through |
social media
workshops |
| gptkbp:is_recognized_by |
NLP community
|
| gptkbp:is_recognized_for |
innovation in QA
|
| gptkbp:is_referenced_in |
gptkb:academic_journals
gptkb:educational_materials tutorials |
| gptkbp:is_related_to |
gptkb:SQu_AD
|
| gptkbp:is_supported_by |
academic institutions
data scientists research funding research grants scholarly articles |
| gptkbp:is_tested_for |
gptkb:various_languages
baseline models diverse populations real-world data various datasets state-of-the-art models |
| gptkbp:is_used_by |
gptkb:researchers
|
| gptkbp:is_used_for |
model comparison
|
| gptkbp:is_used_to |
improve QA systems
|
| gptkbp:is_utilized_for |
language understanding
|
| gptkbp:is_utilized_in |
gptkb:academic_research
gptkb:machine_learning data analysis AI applications |
| gptkbp:performance |
cross-lingual tasks
QA tasks |
| gptkbp:provides |
evaluation metrics
dataset for training |
| gptkbp:published_in |
gptkb:2020
|
| gptkbp:supports |
fine-tuning
|
| gptkbp:bfsParent |
gptkb:XLM-Ro_BERTa
|
| gptkbp:bfsLayer |
6
|