16 papers
Stream-based Online and Offline Monitoring under Measurement Noise
Bernd Finkbeiner, Martin Fränzle, Florian Kohn +1
Stream-based monitoring is a runtime verification approach for cyber-physical systems that translates streams of input data, such as sensor readings, into streams of aggregate stat…
MacrOData: New Benchmarks of Thousands of Datasets for Tabular Outlier Detection
Xueying Ding, Simon Klüttermann, Haomin Wen +2
Quality benchmarks are essential for fairly and accurately tracking scientific progress and enabling practitioners to make informed methodological choices. Outlier detection (OD) o…
Structured Prompt Optimization Meets Reinforcement Learning for Global and Local Interpretability over Complex Text
Tianyang Zhou, Wenbo Chen, Pierre Jinghong Liang +1
LLMs have advanced text classification, yet existing paradigms face a trade-off: supervised (label only) fine-tuning is scalable but offers limited reasoning on complex text and la…
From Zero to Hero: Advancing Zero-Shot Foundation Models for Tabular Outlier Detection
Xueying Ding, Haomin Wen, Simon Klüttermann +1
Outlier detection (OD) is widely used in practice; but its effective deployment on new tasks is hindered by lack of labeled outliers, which makes algorithm and hyperparameter selec…
Activation Steering for Synthetic Data Generation: The Role of Diversity in Downstream Safety Detection
Vijeta Deshpande, Tootiya Giyahchi, Veena Padmanabhan +2
Safety detection models require examples of HHH (Helpful, Harmless, Honest)-violating outputs for robust generalization, however such examples are scarce. Activation Steering (AS)…
Toward Privileged Foundation Models:LUPI for Accelerated and Improved Learning
Xueying Ding, Leman Akoglu
Training foundation models is computationally intensive and often slow to converge. We introduce PIQL,Privileged Information for Quick and Quality Learning, the first framework to…