1 citations · 2 across the 13 of their papers we have counts for
3 papers · 2 filters
Evaluating the Ability of LLMs to Solve Semantics-Aware Process Mining Tasks
Adrian Rebmann, Fabian David Schmidt, Goran Glavaš +1
The process mining community has recently recognized the potential of large language models (LLMs) for tackling various process mining tasks. Initial studies report the capability…
Self-Distillation for Model Stacking Unlocks Cross-Lingual NLU in 200+ Languages
Fabian David Schmidt, Philipp Borchert, Ivan Vulić +1
LLMs have become a go-to solution not just for text generation, but also for natural language understanding (NLU) tasks. Acquiring extensive knowledge through language modeling on…
Knowledge Distillation vs. Pretraining from Scratch under a Fixed (Computation) Budget
Minh Duc Bui, Fabian David Schmidt, Goran Glavaš +1
Compared to standard language model (LM) pretraining (i.e., from scratch), Knowledge Distillation (KD) entails an additional forward pass through a teacher model that is typically…