{"id":35065,"date":"2024-09-10T09:26:32","date_gmt":"2024-09-10T07:26:32","guid":{"rendered":"https:\/\/www.l3s.de\/?page_id=35065"},"modified":"2026-02-10T16:30:14","modified_gmt":"2026-02-10T15:30:14","slug":"best-publications","status":"publish","type":"page","link":"https:\/\/www.l3s.de\/de\/publications\/best-publications\/","title":{"rendered":"Beste Ver\u00f6ffentlichungen"},"content":{"rendered":"
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Das L3S zeichnet regelm\u00e4\u00dfig die Autoren der besten Publikationen des Quartals aus, die auf renommierten Konferenzen (A*) pr\u00e4sentiert oder in hochrangigen Zeitschriften (Q1) ver\u00f6ffentlicht wurden.<\/p>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n

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\n \n \n 2025\/Q3-4<\/span>\n
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AI-Driven Personalized Nutrition: Integrating Omics, Ethics, and Digital Health<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Audio Monitoring of Bone Cement Disintegration in Pulsating Fluid Jet Surgery under Laboratory Conditions<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Breaking the Lens of the Telescope: Online Relevance Estimation over Large Retrieval Sets<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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CHiQPM: Calibrated Hierarchical Interpretable Image Classification<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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ConstrainTree: Enhancing Decision Trees With Semantic Constraint Validation<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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DeepCAVE<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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EmoNet-Face: An Expert-Annotated Benchmark for Synthetic Emotion Recognition<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Enhancing Temporal Understanding in Video-LLMs through Stacked Temporal Attention in Vision Encoders<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Fed-FUEL: fairness and utility enhancing agnostic federated learning framework<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Generalizable and Fast Surrogates: Model Predictive Control of Articulated Soft Robots using Physics-Informed Neural Networks<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Hybrid pathfinding optimization for the Lightning Network with Reinforcement Learning<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Neural Attention Search<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Optimization driven quantum circuit reduction<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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SPAN: Learning Similarity between Scene Graphs and Images with Transformers<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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TCR: Topologically Consistent Reweighting for XGBoost in Regression Tasks<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Towards an Ontology-Driven Approach to Document Bias<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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VANILLA: Validated knowledge graph completion – A Normalization-based framework for Integrity, Link prediction, and Logical Accuracy<\/h5>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n
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\n \n \n 2025\/Q2<\/span>\n
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Aligning Visual Contrastive Learning Models via Preference Optimization<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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AutoML for Multi-Class Anomaly Compensation of Sensor Drift<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Enhancing Online Climate Discourse: A Two-Stage Framework for Climate Content Categorization and Moderation<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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FedFlow: A Personalized Federated Learning Framework for Passenger Flow Prediction<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Interpretable Zero-Shot Stance Detection with Proactive Content Intervention<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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SimE: A Knowledge Graph Embedding Model to Encode Self-Similar Structures Through Algebraic and Geometric Transformations<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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UncertainSAM: Fast and Efficient Uncertainty Quantification of the Segment Anything Model<\/h5>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n
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\n \n \n 2025\/Q1 2024\/Q4<\/span>\n
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ACROSS: A Deformation-Based Cross-Modal Representation for Robotic Tactile Perception<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Explainable Reinforcement Learning via Dynamic Mixture Policies<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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From Genesis to Maturity: Managing Knowledge Graph Ecosystems Through Life Cycles [Vision]<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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QPM: Discrete Optimization for Globally Interpretable Image Classification<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Robust Fusion of Time Series and Image Data for Improved Multimodal Clinical Prediction<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Towards Interpretable Hybrid AI: Integrating Knowledge Graphs and Symbolic Reasoning in Medicine<\/h5>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n
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\n \n \n 2024\/Q3<\/span>\n
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Employing Hybrid AI Systems to Trace and Document Bias in ML Pipelines<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Family history of cancer and lung cancer: Utility of big data and artificial intelligence for exploring the role of genetic risk<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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LaMMOn: language model combined graph neural network for multi-target multi-camera tracking in online scenarios<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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LLM-based Rewriting of Inappropriate Argumentation using Reinforcement Learning from Machine Feedback<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Open benchmark for filtering techniques in entity resolution<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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PALADIN: A process-based constraint language for data validation<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Structure in Deep Reinforcement Learning: A Survey and Open Problems<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Using AI Assistants in Software Development: A Qualitative Study on Security Practices and Concerns<\/h5>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n
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\n \n \n 2024\/Q2<\/span>\n
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Ein vertrauensw\u00fcrdiger Ansatz zur Klassifizierung und Analyse von epidemiebezogenen Informationen aus Microblogs<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Analyse der Sicherheits- und Datenschutzhinweise w\u00e4hrend der russischen Invasion in der Ukraine 2022 auf Twitter<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Jenseits der Genauigkeit: Untersuchung von Fehlertypen in GPT-4-Antworten auf USMLE-Fragen<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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CauseKG: Ein Rahmenwerk zur Verbesserung der kausalen Inferenz mit implizitem Wissen aus Wissensgraphen<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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FLATTEN: optische FLOW-gef\u00fchrte ATTENtion f\u00fcr konsistente Text-zu-Video-Bearbeitung<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Beherrschung von Null-Schuss-Interaktionen in kooperativen und kompetitiven Simultanspielen<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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MEDVOC: Vokabularanpassung zur Feinabstimmung vorab trainierter Sprachmodelle f\u00fcr die Zusammenfassung medizinischer Texte<\/h5>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n
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\n \n \n 2024\/Q1<\/span>\n
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Diagrammatic Reasoning f\u00fcr ALC-Visualisierungen mit Logikgraphen<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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\u201cVersteht\u201c ein Sprachmodell die Mathematik der Oberstufe? Ein \u00dcberblick \u00fcber Deep-Learning-basierte Wortprobleml\u00f6ser<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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FairTrade: Pareto-optimale Kompromisse zwischen ausgewogener Genauigkeit und Fairness beim f\u00f6derierten Lernen<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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IVP-VAE: Modellierung von EHR-Zeitreihen mit Anfangswertprobleml\u00f6sern<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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MTS2Graph: Interpretierbare multivariate Zeitreihenklassifikation mit sich zeitlich entwickelnden Graphen<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Verringerung der CO\u2082-Emissionen in einem verteilten Peer-to-Peer-Zahlungsnetz: Spielt die Geografie im Blitz-Netzwerk eine Rolle?<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Visuo-Haptische Objektwahrnehmung f\u00fcr Roboter: Ein \u00dcberblick<\/h5>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n
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\n \n \n 2023\/Q3-4<\/span>\n
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A neuro-symbolic system over knowledge graphs for link prediction<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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AutoML in Heavily Constrained Applications<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Bridging Qualitative Data Silos: the Potential of Reusing Codings through Machine Learning based Cross-study Code Linking<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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CollabGraph: A graph-based collaborative search summary visualisation.<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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FAC-fed: Federated adaptation for fairness and concept drift aware stream classification<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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FLAMES2Graph: An Interpretable Federated Multivariate Time Series Classification Framework<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Hyperparameters in Reinforcement Learning and How to Tune Them<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Inductive and Transductive Link Prediction for Criminal Network Analysis<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Intensity-Valued Emotions Help Stance Detection of Climate Change Twitter Data<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Modeling Appropriate Language in Argumentation<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Multi-Vehicle Multi-Camera Tracking with Graph-Based Tracklet Features<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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On the relation between dynamic regret and closed-loop stability<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Private Graph Extraction via Feature Explanations<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Ranking facts for explaining answers to elementary science questions<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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To Revise or Not to Revise: Learning to Detect Improvable Claims for Argumentative Writing Support<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Zero-Shot Entailment of Leaderboards for Empirical AI Research<\/h5>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n
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\n \n \n 2023\/Q1-2<\/span>\n
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A message passing framework with multiple data integration for miRNA-disease association prediction<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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DuetCS: Code Style Transfer through Generation and Retrieval<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Efficient Neural Ranking using Forward Indexes<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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How to reduce the search space of Entity Resolution: with Blocking or Nearest Neighbor search?<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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MATE: Multi-Attribute Table Extraction<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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\u201cSecurity is not my field, I\u2019m a stats guy\u201d: A Qualitative Root Cause Analysis of Barriers to Adversarial Machine Learning Defenses in Industry<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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TinyGenius: intertwining natural language processing with microtask crowdsourcing for scholarly knowledge graph creation<\/h5>\n <\/a>\n <\/div>\n <\/div>\n
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Towards an Interpretable Approach to Classify and Summarize Crisis Events from Microblogs<\/h5>\n <\/a>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n <\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"

The L3S regularly honours the authors of the best publications of the quarter, which were presented at renowned conferences (A*) or published in high-ranking journals (Q1). 2025\/Q3-4 AI-Driven Personalized Nutrition: Integrating Omics, Ethics, and Digital Health Audio Monitoring of Bone Cement Disintegration in Pulsating Fluid Jet Surgery under Laboratory Conditions Breaking the Lens of the […]<\/p>","protected":false},"author":11,"featured_media":0,"parent":1284,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-templates\/full-width-page.php","meta":{"_acf_changed":false,"footnotes":""},"categories":[],"tags":[],"class_list":["post-35065","page","type-page","status-publish","hentry"],"acf":[],"aioseo_notices":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-24 23:43:47","action":"category","newStatus":"draft","terms":[75],"taxonomy":"category","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.l3s.de\/de\/wp-json\/wp\/v2\/pages\/35065","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.l3s.de\/de\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.l3s.de\/de\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.l3s.de\/de\/wp-json\/wp\/v2\/users\/11"}],"replies":[{"embeddable":true,"href":"https:\/\/www.l3s.de\/de\/wp-json\/wp\/v2\/comments?post=35065"}],"version-history":[{"count":20,"href":"https:\/\/www.l3s.de\/de\/wp-json\/wp\/v2\/pages\/35065\/revisions"}],"predecessor-version":[{"id":42556,"href":"https:\/\/www.l3s.de\/de\/wp-json\/wp\/v2\/pages\/35065\/revisions\/42556"}],"up":[{"embeddable":true,"href":"https:\/\/www.l3s.de\/de\/wp-json\/wp\/v2\/pages\/1284"}],"wp:attachment":[{"href":"https:\/\/www.l3s.de\/de\/wp-json\/wp\/v2\/media?parent=35065"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.l3s.de\/de\/wp-json\/wp\/v2\/categories?post=35065"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.l3s.de\/de\/wp-json\/wp\/v2\/tags?post=35065"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}