3 citations · 4 across the 7 of their papers we have counts for
7 papers
A systematic Approach to constructing a Chance-and-Risk Matrix for Semiconductor Supply Chains
Ema Salkić, Alexander Fichtl, Philipp Ulrich +3
Semiconductor supply chains face escalating risks from geopolitical tensions, geographic concentration, and rapid technological shifts, yet no scalable system continuously extracts…
MTDiag: A Multi-Turn Diagnostic Dataset Towards Clinically Meaningful LLM Evaluation
Pia Chouayfati, Alexander M. Fichtl, Miriam Anschütz +2
Clinical diagnosis is fundamentally interactive and incremental, yet the dominant paradigm for evaluating Large Language Models (LLMs) in medicine remains static QA benchmarks or t…
AI-Assisted Peer Review Across Research Communities: From Reviewer AI Policies to LLM Review Quality
Alexander M. Fichtl, Lukas Ellinger, Josefin Kelber +2
AI-assisted peer review is increasingly discussed and adopted as a tool to support the scientific publishing process, yet there is little systematic understanding of how publicatio…
Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering
Lukas Ellinger, Alexander Fichtl, Miriam Anschütz +1
Natural language conveys information at varying levels of granularity, from fine-grained references to broad descriptions. While granularity is fundamental to human communication,…
The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
Alexander M. Fichtl, Jeremias Bohn, Josefin Kelber +2
Transformers have dominated sequence processing tasks for the past seven years -- most notably language modeling. However, the inherent quadratic complexity of their attention mech…
Adapter-based Approaches to Knowledge-enhanced Language Models -- A Survey
Alexander Fichtl, Juraj Vladika, Georg Groh
Knowledge-enhanced language models (KELMs) have emerged as promising tools to bridge the gap between large-scale language models and domain-specific knowledge. KELMs can achieve hi…
Diversifying Knowledge Enhancement of Biomedical Language Models using Adapter Modules and Knowledge Graphs
Juraj Vladika, Alexander Fichtl, Florian Matthes
Recent advances in natural language processing (NLP) owe their success to pre-training language models on large amounts of unstructured data. Still, there is an increasing effort t…