59 citations · 71 across the 2 of their papers we have counts for
2 papers
cs.HC2024★ 59 cited
Contextual AI Journaling: Integrating LLM and Time Series Behavioral Sensing Technology to Promote Self-Reflection and Well-being using the MindScape App
Subigya Nepal, Arvind Pillai, William Campbell +11
MindScape aims to study the benefits of integrating time series behavioral patterns (e.g., conversational engagement, sleep, location) with Large Language Models (LLMs) to create a…
cs.CL2023★ 12 cited
RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation
Fangyuan Xu, Weijia Shi, Eunsol Choi
Retrieving documents and prepending them in-context at inference time improves performance of language model (LMs) on a wide range of tasks. However, these documents, often spannin…