25 citations · 28 across the 9 of their papers we have counts for
3 papers · 1 filter
On Epistemic Diversity in Large Language Models
Elisabeth Kirsten, Nicole Krämer, Muhammad Bilal Zafar
Large language models (LLMs) are increasingly used not only to retrieve information, but to answer questions, explain, teach, and support inquiry. In such settings, evaluation cann…
Can LLMs Explain Themselves Counterfactually?
Zahra Dehghanighobadi, Asja Fischer, Muhammad Bilal Zafar
Explanations are an important tool for gaining insights into the behavior of ML models, calibrating user trust and ensuring regulatory compliance. Past few years have seen a flurry…
The Impact of Inference Acceleration on Bias of LLMs
Elisabeth Kirsten, Ivan Habernal, Vedant Nanda +1
Last few years have seen unprecedented advances in capabilities of Large Language Models (LLMs). These advancements promise to benefit a vast array of application domains. However,…