I know you are different! Towards Persona Driven Knowledge-infused Dialogue Assistant.
| Authors | Shifali Agrahari et al. |
| Year | 2026 |
| Venue | EACL 2026 |
| Paper | View on ACL Anthology |
| PDF | Download |
Abstract
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Engineering Breakdown
Plain English
This paper addresses building dialogue assistants that adapt to individual user personas by incorporating knowledge-infused techniques. The work focuses on making conversational AI systems recognize and respond to different user characteristics, personalities, and preferences rather than treating all users uniformly.
Key Engineering Insight
The core insight is that dialogue systems need explicit persona modeling combined with knowledge integration to generate contextually appropriate responses — treating persona as a first-class component of the generation pipeline rather than an afterthought or post-processing step.
Why It Matters for Engineers
Production chatbots and conversational AI systems today still mostly generate generic responses that don't adapt to user identity or context. This research directly addresses the engineering problem of scaling personalized dialogue without massive amounts of user-specific training data, which is critical for enterprise and consumer applications where one-size-fits-all responses degrade user experience.
Research Context
Prior work on dialogue systems treated personalization as optional or bolted-on; this paper advances the field by making persona-driven generation a core design principle. It extends knowledge-grounded dialogue research (which adds factual grounding) to also incorporate persona grounding, enabling systems that are both factually accurate and personally relevant — a capability that's becoming table stakes for competitive conversational AI products.
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