Veronika Solopova, Adrian Gruszczynski, Eiad Rostom, Fritz Cremer, Sascha Witte, Chengming Zhang, Fernando Ramos L'opez Lea Plossl, Florian Hofmann, R. Romeike, Michaela Glaser-Zikuda, C. Benzmuller, Tim Landgraf
{"title":"PapagAI: Automated Feedback for Reflective Essays","authors":"Veronika Solopova, Adrian Gruszczynski, Eiad Rostom, Fritz Cremer, Sascha Witte, Chengming Zhang, Fernando Ramos L'opez Lea Plossl, Florian Hofmann, R. Romeike, Michaela Glaser-Zikuda, C. Benzmuller, Tim Landgraf","doi":"10.48550/arXiv.2307.07523","DOIUrl":"https://doi.org/10.48550/arXiv.2307.07523","url":null,"abstract":"Written reflective practice is a regular exercise pre-service teachers perform during their higher education. Usually, their lecturers are expected to provide individual feedback, which can be a challenging task to perform on a regular basis. In this paper, we present the first open-source automated feedback tool based on didactic theory and implemented as a hybrid AI system. We describe the components and discuss the advantages and disadvantages of our system compared to the state-of-art generative large language models. The main objective of our work is to enable better learning outcomes for students and to complement the teaching activities of lecturers.","PeriodicalId":303369,"journal":{"name":"Deutsche Jahrestagung für Künstliche Intelligenz","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123804215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Martin Glauer, F. Neuhaus, T. Mossakowski, J. Hastings
{"title":"Ontology Pre-training for Poison Prediction","authors":"Martin Glauer, F. Neuhaus, T. Mossakowski, J. Hastings","doi":"10.48550/arXiv.2301.08577","DOIUrl":"https://doi.org/10.48550/arXiv.2301.08577","url":null,"abstract":"Integrating human knowledge into neural networks has the potential to improve their robustness and interpretability. We have developed a novel approach to integrate knowledge from ontologies into the structure of a Transformer network which we call ontology pre-training: we train the network to predict membership in ontology classes as a way to embed the structure of the ontology into the network, and subsequently fine-tune the network for the particular prediction task. We apply this approach to a case study in predicting the potential toxicity of a small molecule based on its molecular structure, a challenging task for machine learning in life sciences chemistry. Our approach improves on the state of the art, and moreover has several additional benefits. First, we are able to show that the model learns to focus attention on more meaningful chemical groups when making predictions with ontology pre-training than without, paving a path towards greater robustness and interpretability. Second, the training time is reduced after ontology pre-training, indicating that the model is better placed to learn what matters for toxicity prediction with the ontology pre-training than without. This strategy has general applicability as a neuro-symbolic approach to embed meaningful semantics into neural networks.","PeriodicalId":303369,"journal":{"name":"Deutsche Jahrestagung für Künstliche Intelligenz","volume":"120 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114087293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Automated Kantian Ethics: A Faithful Implementation","authors":"Lavanya Singh","doi":"10.48550/arXiv.2207.10152","DOIUrl":"https://doi.org/10.48550/arXiv.2207.10152","url":null,"abstract":"As we grant artificial intelligence increasing power and independence in contexts like healthcare, policing, and driving, AI faces moral dilemmas but lacks the tools to solve them. Warnings from regulators, philosophers, and computer scientists about the dangers of unethical artificial intelligence have spurred interest in automated ethics-i.e., the development of machines that can perform ethical reasoning. However, prior work in automated ethics rarely engages with philosophical literature. Philosophers have spent centuries debating moral dilemmas so automated ethics will be most nuanced, consistent, and reliable when it draws on philosophical literature. In this paper, I present an implementation of automated Kantian ethics that is faithful to the Kantian philosophical tradition. I formalize Kant's categorical imperative in Dyadic Deontic Logic, implement this formalization in the Isabelle theorem prover, and develop a testing framework to evaluate how well my implementation coheres with expected properties of Kantian ethic. My system is an early step towards philosophically mature ethical AI agents and it can make nuanced judgements in complex ethical dilemmas because it is grounded in philosophical literature. Because I use an interactive theorem prover, my system's judgements are explainable.","PeriodicalId":303369,"journal":{"name":"Deutsche Jahrestagung für Künstliche Intelligenz","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117306592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christian Löwens, Inaam Ashraf, Alexander Gembus, Genesis Cuizon, Jonas K. Falkner, L. Schmidt-Thieme
{"title":"Solving the Traveling Salesperson Problem with Precedence Constraints by Deep Reinforcement Learning","authors":"Christian Löwens, Inaam Ashraf, Alexander Gembus, Genesis Cuizon, Jonas K. Falkner, L. Schmidt-Thieme","doi":"10.1007/978-3-031-15791-2_14","DOIUrl":"https://doi.org/10.1007/978-3-031-15791-2_14","url":null,"abstract":"","PeriodicalId":303369,"journal":{"name":"Deutsche Jahrestagung für Künstliche Intelligenz","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126089559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unsupervised Alignment of Distributional Word Embeddings","authors":"Aïssatou Diallo","doi":"10.48550/arXiv.2203.04863","DOIUrl":"https://doi.org/10.48550/arXiv.2203.04863","url":null,"abstract":"Cross-domain alignment play a key roles in tasks ranging from machine translation to transfer learning. Recently, purely unsupervised methods operating on monolingual embeddings have successfully been used to infer a bilingual lexicon without relying on supervision. However, current state-of-the art methods only focus on point vectors although distributional embeddings have proven to embed richer semantic information when representing words. In this paper, we propose stochastic optimization approach for aligning probabilistic embeddings. Finally, we evaluate our method on the problem of unsupervised word translation, by aligning word embeddings trained on monolingual data. We show that the proposed approach achieves good performance on the bilingual lexicon induction task across several language pairs and performs better than the point-vector based approach.","PeriodicalId":303369,"journal":{"name":"Deutsche Jahrestagung für Künstliche Intelligenz","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129347971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Leonhard Czarnetzki, Fabian Kainz, Fabian Lächler, Catherine Laflamme, Daniel Bachlechner
{"title":"Enabling Supervised Machine Learning Through Data Pooling: A Case Study with Small and Medium-Sized Enterprises in the Service Industry","authors":"Leonhard Czarnetzki, Fabian Kainz, Fabian Lächler, Catherine Laflamme, Daniel Bachlechner","doi":"10.1007/978-3-031-15791-2_6","DOIUrl":"https://doi.org/10.1007/978-3-031-15791-2_6","url":null,"abstract":"","PeriodicalId":303369,"journal":{"name":"Deutsche Jahrestagung für Künstliche Intelligenz","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115663806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bettina Finzel, David E. Tafler, Stephan Scheele, Ute Schmid
{"title":"Explanation as a Process: User-Centric Construction of Multi-level and Multi-modal Explanations","authors":"Bettina Finzel, David E. Tafler, Stephan Scheele, Ute Schmid","doi":"10.1007/978-3-030-87626-5_7","DOIUrl":"https://doi.org/10.1007/978-3-030-87626-5_7","url":null,"abstract":"","PeriodicalId":303369,"journal":{"name":"Deutsche Jahrestagung für Künstliche Intelligenz","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114839425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. M. Nguyen, T. Mai, Ngoc T. T. Than, Alexander Prange, Daniel Sonntag
{"title":"Self-Supervised Domain Adaptation for Diabetic Retinopathy Grading using Vessel Image Reconstruction","authors":"D. M. Nguyen, T. Mai, Ngoc T. T. Than, Alexander Prange, Daniel Sonntag","doi":"10.1007/978-3-030-87626-5_26","DOIUrl":"https://doi.org/10.1007/978-3-030-87626-5_26","url":null,"abstract":"","PeriodicalId":303369,"journal":{"name":"Deutsche Jahrestagung für Künstliche Intelligenz","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121488997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Randomness of Input Data Spaces is an A Priori Predictor for Generalization","authors":"Martin Briesch, Dominik Sobania, Franz Rothlauf","doi":"10.1007/978-3-031-15791-2_3","DOIUrl":"https://doi.org/10.1007/978-3-031-15791-2_3","url":null,"abstract":"","PeriodicalId":303369,"journal":{"name":"Deutsche Jahrestagung für Künstliche Intelligenz","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126808688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Combining Transformer Generators with Convolutional Discriminators","authors":"R. Durall, Stanislav Frolov, A. Dengel, J. Keuper","doi":"10.1007/978-3-030-87626-5_6","DOIUrl":"https://doi.org/10.1007/978-3-030-87626-5_6","url":null,"abstract":"","PeriodicalId":303369,"journal":{"name":"Deutsche Jahrestagung für Künstliche Intelligenz","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126016365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}