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prof.dr. D. Braun (Daniel)

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BMS-HBE-IEBIS
Ravelijn 3333
d.braun@utwente.nl
+31534897792
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Daniel Braun is an assistant professor at the Department of Industrial Engineering and Business Information Systems (IEBIS) at the University of Twente. Previously, he worked in the Department of Informatics at the Technical University of Munich, where he also received his PhD. Daniel holds a master's degree in Computing Science from the University of Aberdeen and a bachelor's in Computer Science from Saarland University.

His research focuses on the application of Natural Language Processing (NLP) and Artificial Intelligence (AI) in knowledge-intensive processes, with a focus on problems from the legal domain (Legal Tech). More broadly, he is also interested in the general application of NLP and Natural Language Generation (NLG) in the context of businesses and administration.

Organisaties

Publicaties

Jump to: 2024 | 2023 | 2022 | 2021 | 2020

2024

Robustness of generative AI detection: adversarial attacks on black-box neural text detectors (2024)International journal of speech technology (E-pub ahead of print/First online). Fishchuk, V. & Braun, D.https://doi.org/10.1007/s10772-024-10144-2Leveraging Annotator Disagreement for Text Classification (2024)[Working paper › Preprint]. ArXiv.org. Xu, J., Theune, M. & Braun, D.http://10.48550/arXiv.2409.17577Leveraging Annotator Disagreement for Text Classification (2024)In Proceedings of the 7th International Conference on Natural Language and Speech Processing (ICNLSP 2024) (pp. 1-10). Association for Computational Linguistics (ACL). Xu, J., Theune, M. & Braun, D.https://aclanthology.org/2024.icnlsp-1.1KI-gestützte Klauselkontrolle in allgemeinen Geschäftsbedingungen: Wie künstliche Intelligenz dabei helfen kann, den Verbraucherschutz beim Onlineshopping zu stärken (2024)In Jahrbuch Konsum & Verbraucherwissenschaften 2023/2024 (pp. 87-100). Verbraucherzentrale NRW. Braun, D.Why "Artificial Intelligence" Should Not Be Regulated (2024)Digital Government: Research and Practice. Braun, D.https://doi.org/10.1145/3696010I beg to differ: how disagreement is handled in the annotation of legal machine learning data sets (2024)Artificial intelligence and law, 32(3), 839-862. Braun, D.https://doi.org/10.1007/s10506-023-09369-4AGB-DE: A Corpus for the Automated Legal Assessment of Clauses in German Consumer Contracts (2024)In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 10389-10405). Association for Computational Linguistics (ACL). Braun, D. & Matthes, F.https://doi.org/10.18653/v1/2024.acl-long.559Teaching Natural Language Processing in Law School (2024)In Proceedings of the Sixth Workshop on Teaching NLP (pp. 85-90). Association for Computational Linguistics (ACL). Braun, D.https://aclanthology.org/2024.teachingnlp-1.13Twente-BMS-NLP at PerspectiveArg 2024: Combining Bi-Encoder and Cross-Encoder for Argument Retrieval (2024)In Proceedings of the 11th Workshop on Argument Mining (ArgMining 2024) (pp. 164-168). Association for Computational Linguistics (ACL). Zhang, L. & Braun, D.https://doi.org/10.18653/v1/2024.argmining-1.17Exploring Lexical Alignment in a Price Bargain Chatbot (2024)In CUI '24: Proceedings of the 6th ACM Conference on Conversational User Interfaces. Article 40. Association for Computing Machinery. Zhao, Z., Theune, M., Srivastava, S. & Braun, D.https://doi.org/10.1145/3640794.3665576

2023

Efficient Black-Box Adversarial Attacks on Neural Text Detectors (2023)In Proceedings of the 6th International Conference on Natural Language and Speech Processing (ICNLSP-2023) (pp. 78-83). Association for Computational Linguistics (ACL). Fishchuk, V. & Braun, D.https://aclanthology.org/2023.icnlsp-1.8Students' Perspective on AI-Supported Assessment of Open-Ended Questions in Higher Education (2023)In Proceedings of the 15th International Conference on Computer Supported Education (pp. 73-79). Braun., D., Rogetzer., P., Stoica, E. & Kurzhals, H.https://doi.org/10.5220/0011648900003470Investigating Conversational Search Behavior for Domain Exploration (2023)In Advances in Information Retrieval: 45th European Conference on Information Retrieval, ECIR 2023, Dublin, Ireland, April 2–6, 2023, Proceedings, Part II (pp. 608-616). Springer Nature. Schneider, P., Afzal, A., Vladika, J., Braun, D. & Matthes, F.https://doi.org/10.1007/978-3-031-28238-6_52Semantic Label Representations with Lbl2Vec: A Similarity-Based Approach for Unsupervised Text Classification (2023)In Web Information Systems and Technologies: 16th International Conference, WEBIST 2020, November 3–5, 2020, and 17th International Conference, WEBIST 2021, October 26–28, 2021, Virtual Events, Revised Selected Papers (pp. 59-73) (Lecture Notes in Business Information Processing). Springer. Schopf, T., Braun, D. & Matthes, F.https://doi.org/10.1007/978-3-031-24197-0_4Challenges in Domain-Specific Abstractive Summarization and How to Overcome Them (2023)In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - (Volume 3) (pp. 682-689) (Proceedings International Conference on Agents and Artificial Intelligence )ICAART); Vol. 2023). SCITEPRESS. Afzal, A., Vladika, J., Braun, D. & Matthes, F.https://doi.org/10.5220/0011744500003393

2022

Evaluating Unsupervised Text Classification: Zero-Shot and Similarity-Based Approaches (2022)In Proceedings of the 2022 6th International Conference on Natural Language Processing and Information Retrieval (pp. 6–15). Association for Computing Machinery. Schopf, T., Braun, D. & Matthes, F.https://doi.org/10.1145/3582768.3582795Tracking Semantic Shifts in German Court Decisions with Diachronic Word Embeddings (2022)In Proceedings of the Natural Legal Language Processing Workshop 2022 (pp. 218-227). Association for Computational Linguistics (ACL). Braun, D.https://aclanthology.org/2022.nllp-1.19.pdfClause Topic Classification in German and English Standard Form Contracts (2022)In Proceedings of The Fifth Workshop on e-Commerce and NLP (ECNLP 5) (pp. 199-209). Association for Computational Linguistics (ACL). Braun, D. & Matthes, F.https://aclanthology.org/2022.ecnlp-1.23Structured Extraction of Terms and Conditions from German and English Online Shops (2022)In Proceedings of The Fifth Workshop on e-Commerce and NLP (ECNLP 5) (pp. 181-190). Association for Computational Linguistics (ACL). Schamel, T., Braun, D. & Matthes, F.https://aclanthology.org/2022.ecnlp-1.21

2021

NLP for Consumer Protection: Battling Illegal Clauses in German Terms and Conditions in Online Shopping (2021)In Proceedings of the 1st Workshop on NLP for Positive Impact (pp. 93-99). Association for Computational Linguistics (ACL). Braun, D. & Matthes, F.https://doi.org/10.18653/v1/2021.nlp4posimpact-1.10Automated Semantic Analysis, Legal Assessment, and Summarization of Standard Form Contracts (2021)[Thesis › PhD Thesis - Research external, graduation external]. Braun, D.https://mediatum.ub.tum.de/?id=1581193Lbl2Vec: An Embedding-based Approach for Unsupervised Document Retrieval on Predefined Topics (2021)In Proceedings of the 17th International Conference on Web Information Systems and Technologies - WEBIST, (pp. 124-132). Schopf, T., Braun, D. & Matthes, F.https://doi.org/10.5220/0010710300003058

2020

Automatic Detection of Terms and Conditions in German and English Online Shops (2020)In Proceedings of the 16th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST 2020, Budapest, Hungary, November 3-5, 2020 (pp. 233-237). SCITEPRESS. Braun, D. & Matthes, F.https://doi.org/10.5220/0010154302330237Would You Lie To Me Bot? Supporting Decision-Making Processes with Deceiving Virtual Agents (2020)Procedia computer science, 177, 587-592. Braun, D., Bhat, M., Biesdorf, A. & Matthes, F.https://doi.org/10.1016/j.procs.2020.10.083MucLex: A German Lexicon for Surface Realisation (2020)In Proceedings of The 12th Language Resources and Evaluation Conference (LREC 2020), Marseille, 11-16 May 2020 (pp. 4653-4657). European Language Resources Association (ELRA). Klimt, K., Braun, D., Schneider, D. & Matthes, F.

Onderzoeksprofielen

Verbonden aan opleidingen

Vakken collegejaar 2024/2025

Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.

Vakken collegejaar 2023/2024

Lopende projecten

License-Aware Web Crawling for Open Search AI (LAW4OSAI)

The LAW4OSAI (License-Aware Web Crawling for Open Search AI) project aims to enable license-aware crawling of web content by automatically identifying and retrieving content licenses. The goal is to enable open web search filtered by licenses and more importantly the development of open large language models for next-generation search technology, like conversational search or image generation, that respect the rights of authors and copyright. We want to foster and interdisciplinary exchange between legal experts interested in copyright and technology law and the technical parts of the open web search community.

Voltooide projecten

Software Aided Analysis of Terms of Services (SaToS)

The phrase "I have read and understood the terms of service" is often referred to as the biggest lie on the internet. Every time we buy something online, we are confronted with Terms of Services (ToS). However, only a few people actually read these terms, before accepting them, often to their disadvantage. General terms and conditions included in standard form contracts are of significant economic value, as most companies use these terms when entering into contractual relationships with their customers. The interdisciplinary computer and legal science research project SaToS (Software Aided Analysis of ToS) from the chair of Software Engineering for Business Information Systems (sebis) at TU Munich aims to automatically identify Terms of Services and summarise them with regard to their lawfulness and customer friendliness, in a simplified language. In this way, SaToS aims to empower customers to make educated decisions about where to buy or not within seconds, directly addressing the imbalance of powers and fostering the constitutional principle of legal clarity.

Meta Model based Natural Language Generation for Automatic Abstractive Text Summarization (A-SUM)

More than 5000 years after its invention, written language is still the most important medium to document and communicate knowledge. While the production of texts is simplified and accelerated by word processing software, template systems and other technologies, the consumption of texts is still a comparably little by technology supported process. The current state-of-the-art in automatic text summarization are mostly so called extractive methods, which extract the n most important sentences of a text by the means of metrics like TF/IDF. These summaries consist of mostly incoherent sentences. The goal of the BMBF founded Software Campus Project "Meta Model based Natural Language Generation for Automatic Abstractive Text Summarization" (A-SUM) is the creation of coherent, personalized automatic abstractive summaries. Instead of just extracting sentences, A-SUM aims to extract facts from texts and store them in an intermediate, meta model based, structured format. Based on user preferences and contextual information, this information can be personalized. By applying Natural Language Generation techniques, we aim to transform the structured representation of information back to a coherent text, which gives the recipient a quick and tailored overview of the content of the original text.

Vertical Social Software (VSS)

Technology Scouting as a Service (TSaaS)

AI-Supported Legal Review of Terms and Conditions to Strengthen Consumer Protection (AGB-Check)

The advancing digitization is increasingly influencing everyday work in so-called “knowledge-intensive” professions. Software that supports experts in dealing with legal texts and questions is often summarized under the term "Legal Tech". In theory, it can help make legal expertise available more quickly and cheaply, and hence making it more accessible, especially for consumers. In practice, however, the necessary technologies are often only available to commercial actors. The goal of AGB-Check is the development of innovative technologies that support legal knowledge workers in their efforts to represent the interests of consumer in the digital age better and more effectively. Using the example of a specific application - automated legal reviews of terms and conditions - we want to research technologies that: Support experts in dealing with German legal texts by automatically analyzing them semantically and classify them regarding their legality Enables geographically and organizationally separated experts to participate together in the learning and development process of legal expert systems Allow to combine machine learning and rule-based techniques to process German legal texts to in hybrid systems

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