12 citations · 16 across the 4 of their papers we have counts for
4 papers
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…
Faithfulness vs. Plausibility: On the (Un)Reliability of Explanations from Large Language Models
Chirag Agarwal, Sree Harsha Tanneru, Himabindu Lakkaraju
Large Language Models (LLMs) are deployed as powerful tools for several natural language processing (NLP) applications. Recent works show that modern LLMs can generate self-explana…
Quantifying Uncertainty in Natural Language Explanations of Large Language Models
Sree Harsha Tanneru, Chirag Agarwal, Himabindu Lakkaraju
Large Language Models (LLMs) are increasingly used as powerful tools for several high-stakes natural language processing (NLP) applications. Recent prompting works claim to elicit…
Word-Level Explanations for Analyzing Bias in Text-to-Image Models
Alexander Lin, Lucas Monteiro Paes, Sree Harsha Tanneru +2
Text-to-image models take a sentence (i.e., prompt) and generate images associated with this input prompt. These models have created award wining-art, videos, and even synthetic da…