[{"keyword":["MAV navigation","Reinforcement learning","Constrained navigation","Control barrier functions"],"title":"Reinforcement Learning-based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints","quality_controlled":"1","project":[{"name":"Institute for Building Intelligence","_id":"A827C0AA-C7DA-11E9-B0AE-1F4CB252D58D"}],"conference":{"end_date":"2026-11-20","name":"9th Iberian Robotics Conference (ROBOT)","location":"Barcelona","start_date":"2026-11-18"},"type":"conference","year":"2026","author":[{"full_name":"Kirsch, André","first_name":"André","last_name":"Kirsch","id":"229807"},{"orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4579-214X/work/227345663","full_name":"Rexilius, Jan","first_name":"Jan","orcid":"0000-0002-4579-214X","last_name":"Rexilius","id":"245736"}],"_id":"7173","citation":{"apa":"Kirsch, A., & Rexilius, J. (n.d.). Reinforcement Learning-based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints. Presented at the 9th Iberian Robotics Conference (ROBOT), Barcelona.","chicago":"Kirsch, André, and Jan Rexilius. “Reinforcement Learning-Based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints,” n.d.","ama":"Kirsch A, Rexilius J. Reinforcement Learning-based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints.","bibtex":"@inproceedings{Kirsch_Rexilius, title={Reinforcement Learning-based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints}, author={Kirsch, André and Rexilius, Jan} }","short":"A. Kirsch, J. Rexilius, in: n.d.","ieee":"A. Kirsch and J. Rexilius, “Reinforcement Learning-based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints,” presented at the 9th Iberian Robotics Conference (ROBOT), Barcelona.","mla":"Kirsch, André, and Jan Rexilius. Reinforcement Learning-Based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints.","alphadin":"Kirsch, André ; Rexilius, Jan: Reinforcement Learning-based MAV Navigation With Parameterized Waypoints: Incorporating Orientation, Speed Limits, and Corridor Constraints. In:"},"language":[{"iso":"eng"}],"abstract":[{"text":"Reinforcement learning has achieved state-of-the-art performance in MAV control, waypoint flight, and obstacle avoidance. However, existing RL approaches often assume fixed objectives and constraints, with flight behavior largely limited by vehicle dynamics and orientation considered only when required for locomotion. Classical planning and model predictive control handle such constraints explicitly, but require optimization or replanning. This motivates methods that combine learned local control with explicit constraint handling. We combine reinforcement learning with control barrier functions to improve constraint-aware execution. We propose parameterized waypoints that encode orientation, velocity, and corridor constraints. Simulation and real-world experiments show that a single policy can execute different constraint-parameterized navigation scenarios, revealing scenario-dependent trade-offs between traversal time, tracking accuracy, and constraint satisfaction.","lang":"eng"}],"user_id":"220548","date_created":"2026-09-21T14:31:38Z","publication_status":"accepted","status":"public","date_updated":"2026-09-24T12:22:54Z"},{"type":"conference","year":"2026","title":"A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer","quality_controlled":"1","project":[{"name":"Institute for Building Intelligence","_id":"A827C0AA-C7DA-11E9-B0AE-1F4CB252D58D"}],"keyword":["Reinforcement Learning","Hybrid Control","Sim-to-Real","Robotic Manipulation","Inverse Kinematics."],"conference":{"location":"Sapporo","name":"26th International Conference on Control, Automation and Systems (ICCAS)","end_date":"2026-10-30","start_date":"2026-10-27"},"language":[{"iso":"eng"}],"abstract":[{"text":"This paper presents a hybrid control architecture for dynamic robotic picking tasks. The framework combines a Deep Reinforcement Learning policy for high-level interception with a dedicated Inverse Kinematics controller for precise terminal grasping, while mitigating precision limitations of monolithic learning-based approaches. The framework utilizes a Proximal Policy Optimization agent to approach moving targets, seamlessly transitioning to an Inverse Kinematics solver that reduces terminal orientational and positional errors while minimizing cumulative control effort. To facilitate deployment on physical hardware, a robust sim-to-real pipeline incorporating system identification, domain randomization, and latency injection is employed. Experimental results on a physical Franka Emika Panda manipulator validate this hybrid architecture. The system achieves an 80% success rate in pick-and-place tasks, compared to 60.8% for unadapted baselines, with no safety-critical violations such as joint limit breaches or collisions observed during testing.","lang":"eng"}],"user_id":"220548","publication_status":"accepted","date_created":"2026-09-21T16:30:06Z","date_updated":"2026-09-24T12:22:21Z","status":"public","author":[{"orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0009-6800-1273/work/227375528","full_name":"Mayer, Patrick Thomas","first_name":"Patrick Thomas","last_name":"Mayer","orcid":"0009-0009-6800-1273","id":"244831"},{"id":"245736","last_name":"Rexilius","orcid":"0000-0002-4579-214X","first_name":"Jan","full_name":"Rexilius, Jan","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4579-214X/work/227375529"}],"department":[{"_id":"102"}],"_id":"7174","citation":{"short":"P.T. Mayer, J. Rexilius, in: n.d.","alphadin":"Mayer, Patrick Thomas ; Rexilius, Jan: A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer. In:","ieee":"P. T. Mayer and J. Rexilius, “A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer,” presented at the 26th International Conference on Control, Automation and Systems (ICCAS), Sapporo.","mla":"Mayer, Patrick Thomas, and Jan Rexilius. A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer.","bibtex":"@inproceedings{Mayer_Rexilius, title={A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer}, author={Mayer, Patrick Thomas and Rexilius, Jan} }","ama":"Mayer PT, Rexilius J. A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer.","apa":"Mayer, P. T., & Rexilius, J. (n.d.). A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer. Presented at the 26th International Conference on Control, Automation and Systems (ICCAS), Sapporo.","chicago":"Mayer, Patrick Thomas, and Jan Rexilius. “A Hybrid Control Framework Using Reinforcement Learning for Dynamic Robotic Manipulation and Sim-to-Real Transfer,” n.d."}},{"citation":{"short":"P.T. Mayer, J. Rexilius, in: n.d.","alphadin":"Mayer, Patrick Thomas ; Rexilius, Jan: Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control. In:","ieee":"P. T. Mayer and J. Rexilius, “Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control,” presented at the 9th Iberian Robotics Conference (ROBOT) , Barcelona.","mla":"Mayer, Patrick Thomas, and Jan Rexilius. Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control.","bibtex":"@inproceedings{Mayer_Rexilius, title={Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control}, author={Mayer, Patrick Thomas and Rexilius, Jan} }","ama":"Mayer PT, Rexilius J. Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control.","chicago":"Mayer, Patrick Thomas, and Jan Rexilius. “Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control,” n.d.","apa":"Mayer, P. T., & Rexilius, J. (n.d.). Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control. Presented at the 9th Iberian Robotics Conference (ROBOT) , Barcelona."},"_id":"7175","author":[{"id":"244831","first_name":"Patrick Thomas","orcid":"0009-0009-6800-1273","last_name":"Mayer","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0009-6800-1273/work/227375532","full_name":"Mayer, Patrick Thomas"},{"first_name":"Jan","last_name":"Rexilius","orcid":"0000-0002-4579-214X","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4579-214X/work/227375533","full_name":"Rexilius, Jan","id":"245736"}],"department":[{"_id":"102"}],"date_created":"2026-09-21T16:34:09Z","publication_status":"accepted","status":"public","date_updated":"2026-09-24T12:21:26Z","language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"Deep reinforcement learning (RL) policies for robotic control typically overfit to a single hardware configuration. Any change to the kinematic chain breaks the learned mapping and requires complete retraining. This paper investigates whether combining self-attention mechanisms with explicit spatial observations can improve a policy’s adaptability to varying kinematic topologies. We train a single RL agent to control a robotic manipulator across different degrees of freedom (DOF), ranging from a restricted 4-DOF mode to a fully redundant 7-DOF configuration. Instead of fixed-length state vectors, the method processes the active joints as a variable-length sequence in an attention buffer, enriching each joint’s representation with its relative spatial routing and geometric Jacobian influence. This structure allows the agent to dynamically evaluate the physical utility of its available actuators. The proposed Architecture reaches a success rate of 82.1% across trained topologies and 66.6% on unseen configurations, outperforming MLP and generic attention baselines while remaining nearly collisionfree. Finally, we demonstrate successful sim-to-real transfer by deploying the simulation-trained agent on a physical Franka Emika Panda manipulator."}],"user_id":"220548","conference":{"end_date":"2026-11-20","name":"9th Iberian Robotics Conference (ROBOT) ","location":"Barcelona","start_date":"2026-11-18"},"keyword":["Reinforcement Learning","Robotic Manipulation","Morphology Generalization","Sim-to-Real Transfer"],"project":[{"_id":"A827C0AA-C7DA-11E9-B0AE-1F4CB252D58D","name":"Institute for Building Intelligence"}],"quality_controlled":"1","title":"Adapting to Variable Kinematic Configurations: A Causal-Kinematic Attention Approach for Robotic Control","year":"2026","type":"conference"},{"department":[{"_id":"103"}],"author":[{"orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0000-3555-4183/work/221016189","full_name":"Döring, Lina","first_name":"Lina","last_name":"Döring","orcid":"0009-0000-3555-4183","id":"231689"},{"full_name":"Trojahn, Sebastian","last_name":"Trojahn","first_name":"Sebastian"},{"full_name":"Reusch, Pascal","last_name":"Reusch","first_name":"Pascal","id":"223271"}],"editor":[{"full_name":"Behrendt, Fabian","first_name":"Fabian","last_name":"Behrendt"},{"full_name":"Zadek, Hartmut","first_name":"Hartmut","last_name":"Zadek"},{"first_name":"Jettarat","last_name":"Janmontree","full_name":"Janmontree, Jettarat"},{"last_name":"Trojahn","first_name":"Sebastian","full_name":"Trojahn, Sebastian"},{"last_name":"Lang","first_name":"Sebastian","full_name":"Lang, Sebastian"}],"main_file_link":[{"url":"https://opendata.uni-halle.de/bitstream/1981185920/125478/1/DW16_Smart%20Data%20Adapter%20A%20Hybrid%20Pattern-LLM%20Approach.pdf"}],"citation":{"mla":"Döring, Lina, et al. “Smart Data Adapter: A Hybrid Pattern-LLM Approach.” 19th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management, edited by Fabian Behrendt et al., Otto von Guericke University Library, Magdeburg, Germany, 2026, doi:10.25673/123544.","ieee":"L. Döring, S. Trojahn, and P. Reusch, “Smart data adapter: A hybrid pattern-LLM approach,” in 19th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management, Magdeburg, 2026.","alphadin":"Döring, Lina ; Trojahn, Sebastian ; Reusch, Pascal: Smart data adapter: A hybrid pattern-LLM approach. In: Behrendt, F. ; Zadek, H. ; Janmontree, J. ; Trojahn, S. ; Lang, S. (Hrsg.): 19th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management : Otto von Guericke University Library, Magdeburg, Germany, 2026","short":"L. Döring, S. Trojahn, P. Reusch, in: F. Behrendt, H. Zadek, J. Janmontree, S. Trojahn, S. Lang (Eds.), 19th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management, Otto von Guericke University Library, Magdeburg, Germany, 2026.","ama":"Döring L, Trojahn S, Reusch P. Smart data adapter: A hybrid pattern-LLM approach. In: Behrendt F, Zadek H, Janmontree J, Trojahn S, Lang S, eds. 19th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management. Otto von Guericke University Library, Magdeburg, Germany; 2026. doi:10.25673/123544","bibtex":"@inproceedings{Döring_Trojahn_Reusch_2026, title={Smart data adapter: A hybrid pattern-LLM approach}, DOI={10.25673/123544}, booktitle={19th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management}, publisher={Otto von Guericke University Library, Magdeburg, Germany}, author={Döring, Lina and Trojahn, Sebastian and Reusch, Pascal}, editor={Behrendt, Fabian and Zadek, Hartmut and Janmontree, Jettarat and Trojahn, Sebastian and Lang, SebastianEditors}, year={2026} }","chicago":"Döring, Lina, Sebastian Trojahn, and Pascal Reusch. “Smart Data Adapter: A Hybrid Pattern-LLM Approach.” In 19th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management, edited by Fabian Behrendt, Hartmut Zadek, Jettarat Janmontree, Sebastian Trojahn, and Sebastian Lang. Otto von Guericke University Library, Magdeburg, Germany, 2026. https://doi.org/10.25673/123544.","apa":"Döring, L., Trojahn, S., & Reusch, P. (2026). Smart data adapter: A hybrid pattern-LLM approach. In F. Behrendt, H. Zadek, J. Janmontree, S. Trojahn, & S. Lang (Eds.), 19th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management. Magdeburg: Otto von Guericke University Library, Magdeburg, Germany. https://doi.org/10.25673/123544"},"_id":"7068","user_id":"220548","abstract":[{"text":"Adopting digital twin technologies in small andmedium-sized enterprises (SMEs) is often hinderedby heterogeneous, poorly documented productiondata. Current semantic type detection approachesrequire massive labeled datasets making themimpractical for resource-constrained SMEs. Wepropose a zero-shot hybrid framework combiningpattern-based classification with selective largelanguage model (LLM) reasoning formanufacturing-specific data types. The two-stagearchitecture uses rule-based patterns for high-confidence cases, forwarding ambiguous columnsto a multi-step LLM reasoner. Evaluation on fourmanufacturing datasets shows the hybrid approachachieves weighted F1 within 7 24 percentagepoints of pure LLM classification performancewhile reducing LLM invocations by 39% onaverage. Processing time decreased by up to 2.8×.Our framework addresses a critical gap: automated,computationally efficient data type recognition formanufacturing SMEs without requiring trainingdata, contributing to automated simulation anddigital twin construction.","lang":"eng"}],"language":[{"iso":"eng"}],"status":"public","date_updated":"2026-07-20T08:11:01Z","publication":"19th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management","date_created":"2026-07-16T18:51:32Z","publication_status":"published","keyword":["Semantic Data Type Detection","DigitalTwin","Manufacturing SMEs","Zero-shot Learning","Hybrid AI","LLM"],"project":[{"name":"Institute for Data Science Solutions","_id":"f432a2ee-bceb-11ed-a251-a83585c5074d"}],"quality_controlled":"1","title":"Smart data adapter: A hybrid pattern-LLM approach","conference":{"end_date":"2026-06-16","name":"19th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management","location":"Magdeburg","start_date":"2026-06-15"},"doi":"10.25673/123544","type":"conference","publisher":"Otto von Guericke University Library, Magdeburg, Germany","year":"2026"},{"conference":{"name":"INFORMATIKFESTIVAL 2025","location":"Potsdam","end_date":"2025-09-19","start_date":"2025-09-16"},"urn":"urn:nbn:de:hbz:bi10-62353","file":[{"date_created":"2025-10-15T07:02:12Z","access_level":"open_access","date_updated":"2025-10-15T07:02:12Z","creator":"msangel1","success":1,"content_type":"application/pdf","relation":"main_file","file_name":"Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen Ansätze und Ergebnisse aus dem Projekt TRACES.pdf","file_size":14374281,"file_id":"6236"}],"type":"conference","doi":"10.18420/INF2025_121","tmp":{"image":"/images/cc_by_sa.png","legal_code_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","name":"Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0)","short":"CC BY-SA (4.0)"},"author":[{"full_name":"Sangel, Marius","first_name":"Marius","last_name":"Sangel","id":"243822"},{"first_name":"Emilia","last_name":"Bensch","full_name":"Bensch, Emilia"},{"orcid":"0009-0002-6668-2684","last_name":"Brandt-Pook","first_name":"Hans","full_name":"Brandt-Pook, Hans","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0002-6668-2684/work/194297832","id":"206531"},{"first_name":"Timo","last_name":"Röllke","full_name":"Röllke, Timo"},{"full_name":"Markworth, Cedric","last_name":"Markworth","first_name":"Cedric"}],"date_updated":"2026-03-17T15:29:27Z","page":"1363-1371","publication_identifier":{"unknown":["2944-7682"]},"corporate_editor":["Gesellschaft für Informatik e.V."],"file_date_updated":"2025-10-15T07:02:12Z","oa":"1","title":"Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen: Ansätze und Ergebnisse aus dem Projekt TRACES","quality_controlled":"1","project":[{"name":"Institute for Data Science Solutions","_id":"f432a2ee-bceb-11ed-a251-a83585c5074d"}],"keyword":["Machine Learning","Computer Vision","Instance Segmentation","CNNs","YOLACT","Data Augmentation","Waste Classification","Trash Detection","Biowaste Analysis"],"year":"2025","place":"Bonn","has_accepted_license":"1","issue":"366","main_file_link":[{"open_access":"1"}],"_id":"6235","citation":{"chicago":"Sangel, Marius, Emilia Bensch, Hans Brandt-Pook, Timo Röllke, and Cedric Markworth. “Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen: Ansätze und Ergebnisse aus dem Projekt TRACES.” In INFORMATIK 2025, edited by Gesellschaft für Informatik e.V., 1363–71. Bonn, 2025. https://doi.org/10.18420/INF2025_121.","apa":"Sangel, M., Bensch, E., Brandt-Pook, H., Röllke, T., & Markworth, C. (2025). Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen: Ansätze und Ergebnisse aus dem Projekt TRACES. In Gesellschaft für Informatik e.V. (Ed.), INFORMATIK 2025 (pp. 1363–1371). Bonn. https://doi.org/10.18420/INF2025_121","short":"M. Sangel, E. Bensch, H. Brandt-Pook, T. Röllke, C. Markworth, in: Gesellschaft für Informatik e.V. (Ed.), INFORMATIK 2025, Bonn, 2025, pp. 1363–1371.","mla":"Sangel, Marius, et al. “Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen: Ansätze und Ergebnisse aus dem Projekt TRACES.” INFORMATIK 2025, edited by Gesellschaft für Informatik e.V., no. 366, 2025, pp. 1363–71, doi:10.18420/INF2025_121.","ieee":"M. Sangel, E. Bensch, H. Brandt-Pook, T. Röllke, and C. Markworth, “Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen: Ansätze und Ergebnisse aus dem Projekt TRACES,” in INFORMATIK 2025, Potsdam, 2025, no. 366, pp. 1363–1371.","alphadin":"Sangel, Marius ; Bensch, Emilia ; Brandt-Pook, Hans ; Röllke, Timo ; Markworth, Cedric: Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen: Ansätze und Ergebnisse aus dem Projekt TRACES. In: Gesellschaft für Informatik e.V. (Hrsg.): INFORMATIK 2025. Bonn, 2025, S. 1363–1371","ama":"Sangel M, Bensch E, Brandt-Pook H, Röllke T, Markworth C. Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen: Ansätze und Ergebnisse aus dem Projekt TRACES. In: Gesellschaft für Informatik e.V., ed. INFORMATIK 2025. Bonn; 2025:1363-1371. doi:10.18420/INF2025_121","bibtex":"@inproceedings{Sangel_Bensch_Brandt-Pook_Röllke_Markworth_2025, place={Bonn}, title={Automatisierte Erkennung von Störstoffen in Bioabfall mit maschinellem Lernen: Ansätze und Ergebnisse aus dem Projekt TRACES}, DOI={10.18420/INF2025_121}, number={366}, booktitle={INFORMATIK 2025}, author={Sangel, Marius and Bensch, Emilia and Brandt-Pook, Hans and Röllke, Timo and Markworth, Cedric}, editor={Gesellschaft für Informatik e.V.Editor}, year={2025}, pages={1363–1371} }"},"department":[{"_id":"4b2dc5c9-bee3-11eb-b75f-ecc80f94fb21"}],"publication":"INFORMATIK 2025","status":"public","publication_status":"epub_ahead","date_created":"2025-10-15T07:05:27Z","user_id":"243822","language":[{"iso":"ger"}]},{"type":"conference","doi":"10.1109/CITRExCompanion65208.2025.10981492","publisher":"IEEE","year":"2025","title":"Trust Issues in Active Learning and Their Impact on Real-World Applications","quality_controlled":"1","project":[{"name":"Institute for Data Science Solutions","_id":"f432a2ee-bceb-11ed-a251-a83585c5074d"}],"keyword":["Active Learning","Trustworthiness","Evaluation-methods"],"related_material":{"record":[{"status":"public","relation":"later_version","id":"6045"}]},"conference":{"start_date":"2025-03-17","end_date":"2025-03-20","location":"Trondheim, Norway","name":"2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion)"},"user_id":"263827","language":[{"iso":"eng"}],"corporate_editor":["IEEE"],"publication_identifier":{"eisbn":["979-8-3315-1972-8"]},"publication":"2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion)","date_updated":"2026-03-17T15:29:25Z","status":"public","publication_status":"published","page":"1-5","date_created":"2025-05-05T11:39:04Z","author":[{"id":"252434","full_name":"Jaster, Bjarne","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-8362-5369/work/203880018","last_name":"Jaster","orcid":"0000-0002-8362-5369","first_name":"Bjarne"},{"first_name":"Martin","last_name":"Kohlhase","orcid":"0009-0002-9374-0720","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0002-9374-0720/work/203880020","full_name":"Kohlhase, Martin","id":"226669"}],"main_file_link":[{"url":"https://ieeexplore.ieee.org/document/10981492"}],"_id":"5905","citation":{"chicago":"Jaster, Bjarne, and Martin Kohlhase. “Trust Issues in Active Learning and Their Impact on Real-World Applications.” In 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion), edited by IEEE, 1–5. IEEE, 2025. https://doi.org/10.1109/CITRExCompanion65208.2025.10981492.","apa":"Jaster, B., & Kohlhase, M. (2025). Trust Issues in Active Learning and Their Impact on Real-World Applications. In IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion) (pp. 1–5). Trondheim, Norway: IEEE. https://doi.org/10.1109/CITRExCompanion65208.2025.10981492","ama":"Jaster B, Kohlhase M. Trust Issues in Active Learning and Their Impact on Real-World Applications. In: IEEE, ed. 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion). IEEE; 2025:1-5. doi:10.1109/CITRExCompanion65208.2025.10981492","bibtex":"@inproceedings{Jaster_Kohlhase_2025, title={Trust Issues in Active Learning and Their Impact on Real-World Applications}, DOI={10.1109/CITRExCompanion65208.2025.10981492}, booktitle={2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion)}, publisher={IEEE}, author={Jaster, Bjarne and Kohlhase, Martin}, editor={IEEEEditor}, year={2025}, pages={1–5} }","ieee":"B. Jaster and M. 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