5 citations · 8 across the 9 of their papers we have counts for
4 papers · 1 filter
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…
Profiling Bias in LLMs: Stereotype Dimensions in Contextual Word Embeddings
Carolin M. Schuster, Maria-Alexandra Dinisor, Shashwat Ghatiwala +1
Large language models (LLMs) are the foundation of the current successes of artificial intelligence (AI), however, they are unavoidably biased. To effectively communicate the risks…
A Comprehensive Evaluation of Cognitive Biases in LLMs
Simon Malberg, Roman Poletukhin, Carolin M. Schuster +1
We present a large-scale evaluation of 30 cognitive biases in 20 state-of-the-art large language models (LLMs) under various decision-making scenarios. Our contributions include a…
Tuning Into Bias: A Computational Study of Gender Bias in Song Lyrics
Danqing Chen, Adithi Satish, Rasul Khanbayov +2
The application of text mining methods is becoming increasingly prevalent, particularly within Humanities and Computational Social Sciences, as well as in a broader range of discip…