activity
20232026
most citedSemantic similarity prediction is better than other semantic similarity measures

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2026

A Formal Framework for Uncertainty Analysis of Text Generation with Large Language Models

Steffen Herbold, Florian Lemmerich

The generation of texts using Large Language Models (LLMs) is inherently uncertain, with sources of uncertainty being not only the generation of texts, but also the prompt used and…

cs.CY2026

Criminal Liability of Generative Artificial Intelligence Providers for User-Generated Child Sexual Abuse Material

Anamaria Mojica-Hanke, Thomas Goger, Svenja Wölfel +2

The development of more powerful Generative Artificial Intelligence (GenAI) has expanded its capabilities and the variety of outputs. This has introduced significant legal challeng…

cs.SE2024

Legal Aspects for Software Developers Interested in Generative AI Applications

Steffen Herbold, Brian Valerius, Anamaria Mojica-Hanke +2

Recent successes in Generative Artificial Intelligence (GenAI) have led to new technologies capable of generating high-quality code, natural language, and images. The next step is…

cs.CL2023★ 2 cited

Semantic similarity prediction is better than other semantic similarity measures

Steffen Herbold

Semantic similarity between natural language texts is typically measured either by looking at the overlap between subsequences (e.g., BLEU) or by using embeddings (e.g., BERTScore,…

cs.SE2023

An Exploratory Study of Bug-Introducing Changes: Exploring Relationships in Bug-Introducing Changes Towards Causal Understanding

Lukas Schulte, Anamaria Mojica-Hanke, Mario Linares-Vásquez +1

Context: Many studies consider the relation between individual aspects of the software engineering process and bug-introduction, e.g., software testing and code review. These studi…