# Voice CMS: updating the knowledge base of a digital assistant through conversation

arXiv: https://arxiv.org/abs/2505.22303 · HTML: https://mlsanity.com/paper/2505.22303/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use.
- Builds on 5 of its 26 references that are in the map.
- First posted on arXiv 28 May 2025.

## Placed in

- LLM agents and tool use / [General LLM agent frameworks and benchmarks](https://mlsanity.com/agents/general-llm-agent-frameworks-and-benchmarks/)

## Builds on (most cited first, 5 of 5)

- [A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models](https://mlsanity.com/paper/2401.01313/) (2024)
- [Understanding Users' Dissatisfaction with ChatGPT Responses: Types, Resolving Tactics, and the Effect of Knowledge Level](https://mlsanity.com/paper/2311.07434/) (2023)
- [Cognitive Load and Productivity Implications in Human-Chatbot Interaction](https://mlsanity.com/paper/2111.01400/) (2021)
- [Knowledge Triggering, Extraction and Storage via Human-Robot Verbal Interaction](https://mlsanity.com/paper/2104.11170/) (2021)
- [Digital assistant in a point of sales](https://mlsanity.com/paper/2406.04851/) (2024)

## Built on by (most cited first, 1 of 1)

- [Delegating or Doing? Understanding User Behavior in Hybrid Human-Agent Interfaces](https://mlsanity.com/paper/2608.19551/) (2026)

## Abstract (arXiv)

In this study, we propose a solution based on a multi-agent LLM architecture and a voice user interface (VUI) designed to update the knowledge base of a digital assistant. Its usability is evaluated in comparison to a more traditional graphical content management system (CMS), with a focus on understanding the relationship between user preferences and the complexity of the information being provided. The findings demonstrate that, while the overall usability of the VUI is rated lower than the graphical interface, it is already preferred by users for less complex tasks. Furthermore, the quality of content entered through the VUI is comparable to that achieved with the graphical interface, even for highly complex tasks. Obtained qualitative results suggest that a hybrid interface combining the strengths of both approaches could address the key challenges identified during the experiment, such as reducing cognitive load through graphical feedback while maintaining the intuitive nature of voice-based interactions. This work highlights the potential of conversational interfaces as a viable and effective method for knowledge management in specific business contexts.