11 citations · 52 across the 93 of their papers we have counts for
4 papers · 1 filter
When Does Sparsity Mitigate the Curse of Depth in LLMs
Dilxat Muhtar, Xinyuan Song, Sebastian Pokutta +4
Recent work has demonstrated the curse of depth in large language models (LLMs), where later layers contribute less to learning and representation than earlier layers. Such under-u…
S-DAT: A Multilingual, GenAI-Driven Framework for Automated Divergent Thinking Assessment
Jennifer Haase, Paul H. P. Hanel, Sebastian Pokutta
This paper introduces S-DAT (Synthetic-Divergent Association Task), a scalable, multilingual framework for automated assessment of divergent thinking (DT) -a core component of huma…
Has the Creativity of Large-Language Models peaked? An analysis of inter- and intra-LLM variability
Jennifer Haase, Paul H. P. Hanel, Sebastian Pokutta
Following the widespread adoption of ChatGPT in early 2023, numerous studies reported that large language models (LLMs) can match or even surpass human performance in creative task…
Sustainability via LLM Right-sizing
Jennifer Haase, Finn Klessascheck, Jan Mendling +1
Large language models (LLMs) have become increasingly embedded in organizational workflows. This has raised concerns over their energy consumption, financial costs, and data sovere…