7 citations · 8 across the 11 of their papers we have counts for
7 papers · 1 filter
MoVa: Towards Generalizable Classification of Human Morals and Values
Ziyu Chen, Junfei Sun, Chenxi Li +6
Identifying human morals and values embedded in language is essential to empirical studies of communication. However, researchers often face substantial difficulty navigating the d…
Prompting as Scientific Inquiry
Ari Holtzman, Chenhao Tan
Prompting is the primary method by which we study and control large language models. It is also one of the most powerful: nearly every major capability attributed to LLMs-few-shot…
AbsenceBench: Language Models Can't Tell What's Missing
Harvey Yiyun Fu, Aryan Shrivastava, Jared Moore +3
Large language models (LLMs) are increasingly capable of processing long inputs and locating specific information within them, as evidenced by their performance on the Needle in a…
Concept Incongruence: An Exploration of Time and Death in Role Playing
Xiaoyan Bai, Ike Peng, Aditya Singh +1
Consider this prompt "Draw a unicorn with two horns". Should large language models (LLMs) recognize that a unicorn has only one horn by definition and ask users for clarifications,…
Towards a Client-Centered Assessment of LLM Therapists by Client Simulation
Jiashuo Wang, Yang Xiao, Yanran Li +4
Although there is a growing belief that LLMs can be used as therapists, exploring LLMs' capabilities and inefficacy, particularly from the client's perspective, is limited. This wo…
The Impossibility of Fair LLMs
Jacy Anthis, Kristian Lum, Michael Ekstrand +2
The rise of general-purpose artificial intelligence (AI) systems, particularly large language models (LLMs), has raised pressing moral questions about how to reduce bias and ensure…
Ecologically Valid Explanations for Label Variation in NLI
Nan-Jiang Jiang, Chenhao Tan, Marie-Catherine de Marneffe
Human label variation, or annotation disagreement, exists in many natural language processing (NLP) tasks, including natural language inference (NLI). To gain direct evidence of ho…