Papers by Gerhard Heyer
Casting the Same Sentiment Classification Problem (2021.findings-emnlp)
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| Challenge: | Identifying the stance of an argument towards a topic is a fundamental problem in computational argumentation. |
| Approach: | They propose a task where text users are asked to determine if they have the same sentiment . they aim to enable a more topic-agnostic sentiment classification by using Yelp data . |
| Outcome: | The proposed task achieves an accuracy above 83% for category subsets across topics and 89% on average. |
On Classifying whether Two Texts are on the Same Side of an Argument (2021.emnlp-main)
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| Challenge: | Existing approaches to same side stance classification (S3C) require domain knowledge and semantic inference to solve the task. |
| Approach: | They propose to use same side stance classification to predict whether two arguments argue for the same stance for a given pair of arguments. |
| Outcome: | The proposed model fails to generalize both within and across topics and domains when adjusting the sampling strategy to a more adversarial scenario. |
EVALIGN: Visual Evaluation of Translation Alignment Models (2023.eacl-demo)
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| Challenge: | EvAlign is a visual analytics framework for quantitative and qualitative evaluation of automatic translation alignment models. |
| Approach: | They propose to use EvAlign to analyze automatic translation alignment models and compare their performance with other baseline and state-of-the-art models. |
| Outcome: | The framework hosts nine gold standard datasets and the predictions of multiple alignment models. |
ILCM - A Virtual Research Infrastructure for Large-Scale Qualitative Data (L18-1)
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Andreas Niekler, Arnim Bleier, Christian Kahmann, Lisa Posch, Gregor Wiedemann, Kenan Erdogan, Gerhard Heyer, Markus Strohmaier
| Challenge: | iLCM project develops integrated research environment for qualitative data analysis . text mining and text mining tools are extended by "Open Research Computing" |
| Approach: | iLCM project develops integrated research environment for analysis of structured and unstructured data in a "Software as a Service" architecture. |
| Outcome: | iLCM project develops integrated research environment for analysis of structured and unstructured data in a "Software as a Service" architecture. |
Self-Training for Sample-Efficient Active Learning for Text Classification with Pre-Trained Language Models (2024.emnlp-main)
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| Challenge: | Existing methods to train models without labeled data are lacking in supervised tasks . a lack of labeles is the main obstacle to real-world applications . |
| Approach: | They propose a semi-supervised approach that uses a model to obtain pseudo-labels for unlabeled data. |
| Outcome: | The proposed method outperforms the reproduced methods on four text classification benchmarks. |
Page Stream Segmentation with Convolutional Neural Nets Combining Textual and Visual Features (L18-1)
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| Challenge: | (retro-)digitizing paper-based files is a major undertaking for private and public archives and an important task in electronic mailroom applications. |
| Approach: | They propose to use convolutional neural networks to combine image and text features to achieve optimal document separation. |
| Outcome: | The proposed approach achieves an accuracy of 93 % and is considered a state-of-the-art for this task. |
Press Freedom Monitor: Detection of Reported Press and Media Freedom Violations in Twitter and News Articles (2021.emnlp-demo)
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| Challenge: | Press freedom is under constant and increasing attack, even in Europe. |
| Approach: | They introduce a tool that aims to detect reported press and media freedom violations in news articles and tweets. |
| Outcome: | The tool has shown an impressive performance in detecting press and media freedom violations in news articles and tweets. |
Supporting Land Reuse of Former Open Pit Mining Sites using Text Classification and Active Learning (2021.acl-long)
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Christopher Schröder, Kim Bürgl, Yves Annanias, Andreas Niekler, Lydia Müller, Daniel Wiegreffe, Christian Bender, Christoph Mengs, Gerik Scheuermann, Gerhard Heyer
| Challenge: | open pit mines left many regions worldwide inhospitable or uninhabitable . aforementioned information has to be acquired to ensure safety and validity of land reuse . |
| Approach: | They propose a workflow for supporting the post-mining management of former open pit mines in the eastern part of Germany . they use active learning to perform multi-label sentence classification for two categories of restrictions and seven categories of topics . |
| Outcome: | The proposed system supports the post-mining management of former lignite open pit mines in the eastern part of Germany. |