# Evaluating Quality of Chatbots and Intelligent Conversational Agents

arXiv: https://arxiv.org/abs/1704.04579 · HTML: https://mlsanity.com/paper/1704.04579/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Apr 2017.

## Built on by (most cited first, 16 of 16)

- [FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets](https://mlsanity.com/paper/2307.10928/) (2023)
- [Rewarding Chatbots for Real-World Engagement with Millions of Users](https://mlsanity.com/paper/2303.06135/) (2023)
- [A Literature Survey of Recent Advances in Chatbots](https://mlsanity.com/paper/2201.06657/) (2022)
- [Software-Based Dialogue Systems: Survey, Taxonomy and Challenges](https://mlsanity.com/paper/2106.10901/) (2021)
- [TruthBot: An Automated Conversational Tool for Intent Learning, Curated Information Presenting, and Fake News Alerting](https://mlsanity.com/paper/2102.00509/) (2021)
- [A Role-Selected Sharing Network for Joint Machine-Human Chatting Handoff and Service Satisfaction Analysis](https://mlsanity.com/paper/2109.08412/) (2021)
- [Transformer Based Bengali Chatbot Using General Knowledge Dataset](https://mlsanity.com/paper/2111.03937/) (2021)
- [Task-oriented Dialogue Systems: performance vs. quality-optima, a review](https://mlsanity.com/paper/2112.11176/) (2021)
- [ReSURE: Regularizing Supervision Unreliability for Multi-turn Dialogue Fine-tuning](https://mlsanity.com/paper/2508.19996/) (2025)
- [AI Chatbots as Multi-Role Pedagogical Agents: Transforming Engagement in CS Education](https://mlsanity.com/paper/2308.03992/) (2023)
- [What if AI systems weren't chatbots?](https://mlsanity.com/paper/2605.07896/) (2026)
- [Spoken Humanoid Embodied Conversational Agents in Mobile Serious Games: A Usability Assessment](https://mlsanity.com/paper/2309.07773/) (2023)
- [Consistency of Compositional Generalization across Multiple Levels](https://mlsanity.com/paper/2412.13636/) (2024)
- [HumAIne-Chatbot: Real-Time Personalized Conversational AI via Reinforcement Learning](https://mlsanity.com/paper/2509.04303/) (2025)
- [Causal Inference for Chatting Handoff](https://mlsanity.com/paper/2210.02862/) (2022)
- [Assessing the Applicability of Existing Design Recommendations to AI Companion Design: A Multi-Method Study](https://mlsanity.com/paper/2609.14236/) (2026)

## Abstract (arXiv)

Chatbots are one class of intelligent, conversational software agents activated by natural language input (which can be in the form of text, voice, or both). They provide conversational output in response, and if commanded, can sometimes also execute tasks. Although chatbot technologies have existed since the 1960s and have influenced user interface development in games since the early 1980s, chatbots are now easier to train and implement. This is due to plentiful open source code, widely available development platforms, and implementation options via Software as a Service (SaaS). In addition to enhancing customer experiences and supporting learning, chatbots can also be used to engineer social harm - that is, to spread rumors and misinformation, or attack people for posting their thoughts and opinions online. This paper presents a literature review of quality issues and attributes as they relate to the contemporary issue of chatbot development and implementation. Finally, quality assessment approaches are reviewed, and a quality assessment method based on these attributes and the Analytic Hierarchy Process (AHP) is proposed and examined.