  Despite a surge collection of XAI methods, users still struggle to obtain
required AI explanations. Previous research suggests chatbots as dynamic
solutions, but the effective design of conversational XAI agents for practical
human needs remains under-explored. This paper focuses on Conversational XAI
for AI-assisted scientific writing tasks. Drawing from human linguistic
theories and formative studies, we identify four design rationales:
"multifaceted", "controllability", "mix-initiative", "context-aware
drill-down". We incorporate them into an interactive prototype, ConvXAI, which
facilitates heterogeneous AI explanations for scientific writing through
dialogue. In two studies with 21 users, ConvXAI outperforms a GUI-based
baseline on improving human-perceived understanding and writing improvement.
The paper further discusses the practical human usage patterns in interacting
with ConvXAI for scientific co-writing.
