49 citations · 54 across the 9 of their papers we have counts for
13 papers
GECTurk: Grammatical Error Correction and Detection Dataset for Turkish
Atakan Kara, Farrin Marouf Sofian, Andrew Bond +1
Grammatical Error Detection and Correction (GEC) tools have proven useful for native speakers and second language learners. Developing such tools requires a large amount of paralle…
Benchmarking Procedural Language Understanding for Low-Resource Languages: A Case Study on Turkish
Arda Uzunoglu, Gözde Gül Şahin
Understanding procedural natural language (e.g., step-by-step instructions) is a crucial step to execution and planning. However, while there are ample corpora and downstream tasks…
Metric-Based In-context Learning: A Case Study in Text Simplification
Subha Vadlamannati, Gözde Gül Şahin
In-context learning (ICL) for large language models has proven to be a powerful approach for many natural language processing tasks. However, determining the best method to select…
UKP-SQUARE: An Online Platform for Question Answering Research
Tim Baumgärtner, Kexin Wang, Rachneet Sachdeva +10
Recent advances in NLP and information retrieval have given rise to a diverse set of question answering tasks that are of different formats (e.g., extractive, abstractive), require…
MetaQA: Combining Expert Agents for Multi-Skill Question Answering
Haritz Puerto, Gözde Gül Şahin, Iryna Gurevych
The recent explosion of question answering (QA) datasets and models has increased the interest in the generalization of models across multiple domains and formats by either trainin…
On the rate of convergence of a classifier based on a Transformer encoder
Iryna Gurevych, Michael Kohler, Gözde Gül Sahin
Pattern recognition based on a high-dimensional predictor is considered. A classifier is defined which is based on a Transformer encoder. The rate of convergence of the misclassifi…
To Augment or Not to Augment? A Comparative Study on Text Augmentation Techniques for Low-Resource NLP
Gözde Gül Şahin
Data-hungry deep neural networks have established themselves as the standard for many NLP tasks including the traditional sequence tagging ones. Despite their state-of-the-art perf…
PuzzLing Machines: A Challenge on Learning From Small Data
Gözde Gül Şahin, Yova Kementchedjhieva, Phillip Rust +1
Deep neural models have repeatedly proved excellent at memorizing surface patterns from large datasets for various ML and NLP benchmarks. They struggle to achieve human-like thinki…
Two Birds with One Stone: Investigating Invertible Neural Networks for Inverse Problems in Morphology
Gözde Gül Şahin, Iryna Gurevych
Most problems in natural language processing can be approximated as inverse problems such as analysis and generation at variety of levels from morphological (e.g., cat+Plural <-> c…
LINSPECTOR WEB: A Multilingual Probing Suite for Word Representations
Max Eichler, Gözde Gül Şahin, Iryna Gurevych
We present LINSPECTOR WEB, an open source multilingual inspector to analyze word representations. Our system provides researchers working in low-resource settings with an easily ac…
Text Processing Like Humans Do: Visually Attacking and Shielding NLP Systems
Steffen Eger, Gözde Gül Şahin, Andreas Rücklé +6
Visual modifications to text are often used to obfuscate offensive comments in social media (e.g., "!d10t") or as a writing style ("1337" in "leet speak"), among other scenarios. W…
LINSPECTOR: Multilingual Probing Tasks for Word Representations
Gözde Gül Şahin, Clara Vania, Ilia Kuznetsov +1
Despite an ever growing number of word representation models introduced for a large number of languages, there is a lack of a standardized technique to provide insights into what i…
Character-Level Models versus Morphology in Semantic Role Labeling
Gözde Gül Şahin, Mark Steedman
Character-level models have become a popular approach specially for their accessibility and ability to handle unseen data. However, little is known on their ability to reveal the u…