Papers by Çağrı Çöltekin

7 papers
A Treebank of Asia Minor Greek (2024.lrec-main)

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Challenge: Asia Minor Greek (AMG) dialects are endangered because of declining speaker base and scarce linguistic resources.
Approach: They propose to annotate a treebank of Pharasiot Greek, one of the Asia Minor Greek (AMG) dialects.
Outcome: The proposed treebank consists of 350 sentences from six fairy tales in Pharasiot Greek.
CoNLL-UL: Universal Morphological Lattices for Universal Dependency Parsing (L18-1)

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Challenge: Using the universal dependencies framework, we address the need for a universal representation of morphological analysis that can capture alternative morphology of surface tokens and is compatible with the segmentation and morphologic annotation guidelines prescribed for UD treebanks.
Approach: They propose a new annotation format for word lattices that represent morphological analyses and a resource that obeys this format for a range of typologically different languages.
Outcome: The proposed model can capture alternative morphological analyses of surface tokens and is compatible with the segmentation and morphology guidelines prescribed for UD treebanks.
A Corpus of Turkish Offensive Language on Social Media (2020.lrec-1)

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Challenge: Identifying abusive, offensive, aggressive or in general inappropriate language has recently attracted interest of researchers from academic as well as commercial institutions.
Approach: They propose to classify Turkish offensive language corpus using state-of-the-art annotation methods . they find 19 % of tweets contain some type of offensive language .
Outcome: The proposed corpus of Turkish offensive language is the first of its kind in the world . the results show that 19 % of the tweets contain some type of offensive language .
Multimodal Fact-Checking with Vision Language Models: A Probing Classifier based Solution with Embedding Strategies (2025.coling-main)

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Challenge: Existing fact-checking systems that use text and image information are susceptible to fake news spread by social media platforms.
Approach: They propose a neural probing classifier based on multimodality and embeddings from text and image encoders to represent multimodal content for fact-checking.
Outcome: The proposed classifier outperforms KNN and SVM baselines in leveraging extracted embeddings, highlighting its effectiveness for multimodal fact-checking.
CoRoSeOf - An Annotated Corpus of Romanian Sexist and Offensive Tweets (2022.lrec-1)

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Challenge: Using CoRoSeOf, we manually annotate social media for sexist and offensive language.
Approach: They introduce a large corpus of Romanian social media manually annotated for sexist and offensive language.
Outcome: The proposed corpus contains 39 245 tweets annotated by multiple annotators with an agreement rate of Fleiss’= 0.45 .
Cross-Lingual Learning vs. Low-Resource Fine-Tuning: A Case Study with Fact-Checking in Turkish (2024.lrec-main)

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Challenge: Currently, most of the research on misinformation is focused on the English language . however, there is a scarcity of datasets for other languages, including Turkish .
Approach: They propose a dataset that spans multiple domains and incorporates evidence from three Turkish fact-checking organizations.
Outcome: The proposed dataset has the potential to advance research in the Turkish language.
Reproduction and Replication: A Case Study with Automatic Essay Scoring (2020.lrec-1)

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Challenge: reproducibility of experiments has gained more attention in the NLP community . recent negative reproduction results indicate that published results are not verifiable .
Approach: They propose to reproduce an earlier study of automatic essay scoring for determining the proficiency of second language learners in a multilingual setting.
Outcome: The proposed reproduction of an AES system for determining the proficiency of second language learners in a multilingual setting is compared with the original.

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