activity
20182025
most citedRevisiting the tree edit distance and its backtracing: A tutorial

7 citations · 8 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL2025

Limits of LLM Text Detectors in Education

Lukas Gehring, Benjamin Paaßen

Students increasingly use the assistance of large language models (LLMs) in their academic writing. While slight assistance (e.g., grammar and style correction, as well as feedback…

cs.LG2025

Diffusion Classifier Guidance for Non-robust Classifiers

Philipp Vaeth, Dibyanshu Kumar, Benjamin Paassen +1

Classifier guidance is intended to steer a diffusion process such that a given classifier reliably recognizes the generated data point as a certain class. However, most classifier…

cs.CY2025

Healthy Distrust in AI systems

Benjamin Paaßen, Suzana Alpsancar, Tobias Matzner +1

Under the slogan of trustworthy AI, much of contemporary AI research is focused on designing AI systems and usage practices that inspire human trust and, thus, enhance adoption of…

cs.LG2024

Generative Example-Based Explanations: Bridging the Gap between Generative Modeling and Explainability

Philipp Vaeth, Alexander M. Fruehwald, Benjamin Paassen +1

Recently, several methods have leveraged deep generative modeling to produce example-based explanations of image classifiers. Despite producing visually stunning results, these met…

cs.LG2024

GradCheck: Analyzing classifier guidance gradients for conditional diffusion sampling

Philipp Vaeth, Alexander M. Fruehwald, Benjamin Paassen +1

To sample from an unconditionally trained Denoising Diffusion Probabilistic Model (DDPM), classifier guidance adds conditional information during sampling, but the gradients from c…

cs.CV2023★ 1 cited

Diffusion-based Visual Counterfactual Explanations -- Towards Systematic Quantitative Evaluation

Philipp Vaeth, Alexander M. Fruehwald, Benjamin Paassen +1

Latest methods for visual counterfactual explanations (VCE) harness the power of deep generative models to synthesize new examples of high-dimensional images of impressive quality.…

cs.AI2021

An A*-algorithm for the Unordered Tree Edit Distance with Custom Costs

Benjamin Paaßen

The unordered tree edit distance is a natural metric to compute distances between trees without intrinsic child order, such as representations of chemical molecules. While the unor…

cs.DS2018★ 7 cited

Revisiting the tree edit distance and its backtracing: A tutorial

Benjamin Paaßen

Almost 30 years ago, Zhang and Shasha (1989) published a seminal paper describing an efficient dynamic programming algorithm computing the tree edit distance, that is, the minimum…