activity
20192024
most citedTexPrax: A Messaging Application for Ethical, Real-time Data Collection and Annotation

1 citations · 2 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL2024

Constrained C-Test Generation via Mixed-Integer Programming

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. In contrast…

cs.CL2023

Rediscovering Hashed Random Projections for Efficient Quantization of Contextualized Sentence Embeddings

Ulf A. Hamster, Ji-Ung Lee, Alexander Geyken +1

Training and inference on edge devices often requires an efficient setup due to computational limitations. While pre-computing data representations and caching them on a server can…

cs.CL20231 cited

Lessons Learned from a Citizen Science Project for Natural Language Processing

Jan-Christoph Klie, Ji-Ung Lee, Kevin Stowe +6

Many Natural Language Processing (NLP) systems use annotated corpora for training and evaluation. However, labeled data is often costly to obtain and scaling annotation projects is…

cs.CL20221 cited

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

Lorenz Stangier, Ji-Ung Lee, Yuxi Wang +4

Collecting and annotating task-oriented dialog data is difficult, especially for highly specific domains that require expert knowledge. At the same time, informal communication cha…

cs.CL2021

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

Tilman Beck, Ji-Ung Lee, Christina Viehmann +3

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 s…

cs.CL2020

Empowering Active Learning to Jointly Optimize System and User Demands

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. However, when active l…