Wolter / Schwalbe KI 2026: Advances in Artificial Intelligence

49th German Conference on AI, KI 2026, Bremen, Germany, August 11–14, 2026, Proceedings
Erscheinungsjahr 2026
ISBN: 978-3-032-32335-4
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 348 Seiten

Reihe: Lecture Notes in Artificial Intelligence

This book constitutes the proceedings of the 49th German Conference on Artificial Intelligence (Künstliche Intelligenz), KI 2026, which was held in Bremen, Germany, August 11–16, 2026, Proceedings

The 12 full papers, 19 short papers and 1 extended abstracts presented in these proceedings were carefully reviewed and selected from 78 submissions. They focus on new research results on theory and applications in AI. The papers were categorized in the following sections: Full Technical Papers; Technical Communications; Extended Abstracts.

Zielgruppe

Research

Autoren/Hrsg.

Wolter, Diedrich

Schwalbe, Gesina

Inhaltsverzeichnis

.- Full Papers.
.- A Constraint-based Stockyard Planning Problem on a Realistic Time-Dependent Setting.
.- !Imperio, smolVLA: The Implications of Data Poisoning on Open Source Robotics.
.- SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning.
.- Integrating Insertion Heuristics into the Miller-Tucker-Zemlin Constraint Model for the Traveling Salesperson Problem.
.- Multi-State PatchCore for Noisy Industrial Audio.
.- Prioritizing Conflicts in Conflict-Based Search with Disjoint Splitting.
.- Characteristics, Convergence and Divergence of Modular Semantics for Bipolar Weighted Argumentation Graphs.
.- Do We Really Need Diffusion? A Fast U-Net for Paired Medical ImageTranslation.
.- Achieving Fairness in Repeated Combinatorial Problems through Deep Reinforcement Learning.
.- Successfully Defending Academic Integrity: an Ensemble Approach Towards Detecting Machine-generated Texts.
.- Bias Leaves a Gradient Trail: Label-Free Bias Identification via Gradient Probes on Concept Decompositions.
.- c-Core Revision for Conditional Belief Bases.
.- Technical Communications.
.- Do Flat Representation Manifolds lead to Improved Accuracy?.
.- Explainable Artificial Intelligence in Digital Ecosystems in Research and Education.
.- Comparison of the Runtime of two Algorithms for the Linear Decomposition of ReLU Networks.
.- Evaluating AI as Part of Social Mechanisms.
.- Safeguards for Speech2Speech LLM-Assistants: A Case Study in Automotive Applications..
.- From Large Language Model Predicates to Logic Tensor Networks: Neurosymbolic Offer Validation in Regulated Procurement.
.- Quantum Temporal Convolution Network.
.- Constrained Entity Selection under Partial Knowledge for LLM-Based Knowledge Graph QA.
.- Qualitative Comparison between Marker-Based and Video-Based Human Pose Estimation in the context of Imitation Learning.
.- Multi-Species Mixing for Weakly Supervised SED under Domain Shift.
.- Code Generation for Open Data Statistics: Case Study on the Genesis Database.
.- A Comparison of Repositioning and Scheduling Algorithms for the Ride-Hailing Problem.
.- An Ontology-Grounded Representation for Defeasible Professional Ethics Analysis.
.- WaLo2D: Testbed for Multi-Agent Warehouse Logistics Reinforcement Learning Experiments.
.- PictSure: Pretraining Embeddings Matters for In-Context Learning Image Classifiers.
.- Explainable-AI-Based Training for Relevance-based Robust Reinforcement Learning,
.- Can We Predict LLM Reasoning Failures? Structural Predictability of Modal and Conditional Inference Errors.
.- Neuro-Symbolic Verification of LLM Outputs for Data-Sensitive Domains.
.- A Hybrid Approach for Generating Planning Models from Texts.
.- Extended Abstracts.
.- Efficient Time-Series Approximation with Linear Recurrent Neural Networks.