Entity recognition models detect ads in RAG responses effectively and stay robust when advertisers switch styles, while lightweight models like random forests and SVMs become brittle under the same changes.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
Mixed-methods research shows collective care practices are constrained by personal, relational, technological, and structural factors in existing PHI systems, leading to the CC-Proact operational map with three design levers and ten recommendations for collective health informatics.
citing papers explorer
-
Detecting RAG Advertisements Across Advertising Styles
Entity recognition models detect ads in RAG responses effectively and stay robust when advertisers switch styles, while lightweight models like random forests and SVMs become brittle under the same changes.
-
Unpacking "Personal" Health Informatics for Proactive Collective Care
Mixed-methods research shows collective care practices are constrained by personal, relational, technological, and structural factors in existing PHI systems, leading to the CC-Proact operational map with three design levers and ten recommendations for collective health informatics.