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Christopher Schröder

4 accepted papers

2024

Self-Training for Sample-Efficient Active Learning for Text Classification with Pre-Trained Language Models

EMNLP 2024main

Active learning is an iterative labeling process that is used to obtain a small labeled subset, despite the absence of labeled data, thereby enabling to train a model for supervised tasks such as text classification.While active learning has made considerable progress in recent years due to improvem…

2023

Trigger Warning Assignment as a Multi-Label Document Classification Problem

ACL 2023long

A trigger warning is used to warn people about potentially disturbing content. We introduce trigger warning assignment as a multi-label classification task, create the Webis Trigger Warning Corpus 2022, and with it the first dataset of 1 million fanfiction works from Archive of our Own with up to 36…

2022

Revisiting Uncertainty-based Query Strategies for Active Learning with Transformers

ACL 2022findings

Active learning is the iterative construction of a classification model through targeted labeling, enabling significant labeling cost savings. As most research on active learning has been carried out before transformer-based language models (“transformers”) became popular, despite its practical impo…

2021

Supporting Land Reuse of Former Open Pit Mining Sites using Text Classification and Active Learning

ACL 2021long

Open pit mines left many regions worldwide inhospitable or uninhabitable. Many sites are left behind in a hazardous or contaminated state, show remnants of waste, or have other restrictions imposed upon them, e.g., for the protection of human or nature. Such information has to be permanently managed…