7 citations · 8 across the 4 of their papers we have counts for
4 papers
Prototype Language Models
Dan Ley, Giang Nguyen, Himabindu Lakkaraju +1
Knowing which training examples drive outputs is fundamental to auditing, correcting, and understanding language models, yet for modern LLMs this remains expensive, approximate, an…
Generalized Group Data Attribution
Dan Ley, Suraj Srinivas, Shichang Zhang +2
Data Attribution (DA) methods quantify the influence of individual training data points on model outputs and have broad applications such as explainability, data selection, and noi…
On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models
Sree Harsha Tanneru, Dan Ley, Chirag Agarwal +1
As Large Language Models (LLMs) are increasingly being employed in real-world applications in critical domains such as healthcare, it is important to ensure that the Chain-of-Thoug…
In-Context Explainers: Harnessing LLMs for Explaining Black Box Models
Nicholas Kroeger, Dan Ley, Satyapriya Krishna +2
Recent advancements in Large Language Models (LLMs) have demonstrated exceptional capabilities in complex tasks like machine translation, commonsense reasoning, and language unders…