50 citations · 96 across the 16 of their papers we have counts for
7 papers · 1 filter
Large Language Models Suffer From Their Own Output: An Analysis of the Self-Consuming Training Loop
Martin Briesch, Dominik Sobania, Franz Rothlauf
Large Language Models (LLM) are already widely used to generate content for a variety of online platforms. As we are not able to safely distinguish LLM-generated content from human…
Do You Trust ChatGPT? -- Perceived Credibility of Human and AI-Generated Content
Martin Huschens, Martin Briesch, Dominik Sobania +1
This paper examines how individuals perceive the credibility of content originating from human authors versus content generated by large language models, like the GPT language mode…
Untangling the Effects of Down-Sampling and Selection in Genetic Programming
Ryan Boldi, Ashley Bao, Martin Briesch +4
Genetic programming systems often use large training sets to evaluate the quality of candidate solutions for selection, which is often computationally expensive. Down-sampling trai…
Down-Sampled Epsilon-Lexicase Selection for Real-World Symbolic Regression Problems
Alina Geiger, Dominik Sobania, Franz Rothlauf
Epsilon-lexicase selection is a parent selection method in genetic programming that has been successfully applied to symbolic regression problems. Recently, the combination of rand…
MTGP: Combining Metamorphic Testing and Genetic Programming
Dominik Sobania, Martin Briesch, Philipp Röchner +1
Genetic programming is an evolutionary approach known for its performance in program synthesis. However, it is not yet mature enough for a practical use in real-world software deve…
An Analysis of the Automatic Bug Fixing Performance of ChatGPT
Dominik Sobania, Martin Briesch, Carol Hanna +1
To support software developers in finding and fixing software bugs, several automated program repair techniques have been introduced. Given a test suite, standard methods usually e…
Informed Down-Sampled Lexicase Selection: Identifying productive training cases for efficient problem solving
Ryan Boldi, Martin Briesch, Dominik Sobania +5
Genetic Programming (GP) often uses large training sets and requires all individuals to be evaluated on all training cases during selection. Random down-sampled lexicase selection…