Search Results for author: Ji-Ung Lee

Found 13 papers, 10 papers with code

Constrained C-Test Generation via Mixed-Integer Programming

1 code implementation12 Apr 2024 Ji-Ung Lee, Marc E. Pfetsch, Iryna Gurevych

This work proposes a novel method to generate C-Tests; a deviated form of cloze tests (a gap filling exercise) where only the last part of a word is turned into a gap.

Surveying (Dis)Parities and Concerns of Compute Hungry NLP Research

no code implementations29 Jun 2023 Ji-Ung Lee, Haritz Puerto, Betty van Aken, Yuki Arase, Jessica Zosa Forde, Leon Derczynski, Andreas Rücklé, Iryna Gurevych, Roy Schwartz, Emma Strubell, Jesse Dodge

Many recent improvements in NLP stem from the development and use of large pre-trained language models (PLMs) with billions of parameters.

Transformers with Learnable Activation Functions

2 code implementations30 Aug 2022 Haishuo Fang, Ji-Ung Lee, Nafise Sadat Moosavi, Iryna Gurevych

In contrast to conventional, predefined activation functions, RAFs can adaptively learn optimal activation functions during training according to input data.

TexPrax: A Messaging Application for Ethical, Real-time Data Collection and Annotation

1 code implementation16 Aug 2022 Lorenz Stangier, Ji-Ung Lee, Yuxi Wang, Marvin Müller, Nicholas Frick, Joachim Metternich, Iryna Gurevych

We evaluate TexPrax in a user-study with German factory employees who ask their colleagues for solutions on problems that arise during their daily work.

Chatbot Sentence

Annotation Curricula to Implicitly Train Non-Expert Annotators

1 code implementation CL (ACL) 2022 Ji-Ung Lee, Jan-Christoph Klie, Iryna Gurevych

Annotation studies often require annotators to familiarize themselves with the task, its annotation scheme, and the data domain.


Investigating label suggestions for opinion mining in German Covid-19 social media

1 code implementation ACL 2021 Tilman Beck, Ji-Ung Lee, Christina Viehmann, Marcus Maurer, Oliver Quiring, Iryna Gurevych

This work investigates the use of interactively updated label suggestions to improve upon the efficiency of gathering annotations on the task of opinion mining in German Covid-19 social media data.

Opinion Mining Transfer Learning

Empowering Active Learning to Jointly Optimize System and User Demands

1 code implementation ACL 2020 Ji-Ung Lee, Christian M. Meyer, Iryna Gurevych

Existing approaches to active learning maximize the system performance by sampling unlabeled instances for annotation that yield the most efficient training.

Active Learning

Manipulating the Difficulty of C-Tests

1 code implementation ACL 2019 Ji-Ung Lee, Erik Schwan, Christian M. Meyer

We propose two novel manipulation strategies for increasing and decreasing the difficulty of C-tests automatically.

Text Processing Like Humans Do: Visually Attacking and Shielding NLP Systems

1 code implementation NAACL 2019 Steffen Eger, Gözde Gül Şahin, Andreas Rücklé, Ji-Ung Lee, Claudia Schulz, Mohsen Mesgar, Krishnkant Swarnkar, Edwin Simpson, Iryna Gurevych

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.

Adversarial Attack Sentence

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