Tartan: A retrieval-based socialbot powered by a dynamic finite-state machine architecture
Not on the map. Why?
Abstract (arXiv)
This paper describes the Tartan conversational agent built for the 2018 Alexa Prize Competition. Tartan is a non-goal-oriented socialbot focused around providing users with an engaging and fluent casual conversation. Tartan's key features include an emphasis on structured conversation based on flexible finite-state models and an approach focused on understanding and using conversational acts. To provide engaging conversations, Tartan blends script-like yet dynamic responses with data-based generative and retrieval models. Unique to Tartan is that our dialog manager is modeled as a dynamic Finite State Machine. To our knowledge, no other conversational agent implementation has followed this specific structure.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Dec 2018.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 2; 2022: 3.
5 papers.
- 2021Anticipating Safety Issues in E2E Conversational AI: Framework and Toolingcited by 77
- 2021DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialoguescited by 25
- 2022Do You Know My Emotion? Emotion-Aware Strategy Recognition towards a Persuasive Dialogue Systemcited by 1
- 2022Mining Duplicate Questions of Stack Overflowcited by 0
- 2022Modular Approach to Machine Reading Comprehension: Mixture of Task-Aware Expertscited by 0
- 2022Modular Approach to Machine Reading Comprehension: Mixture of Task-Aware Experts4 Oct 2022
- 2022Mining Duplicate Questions of Stack Overflow4 Oct 2022
- 2022Do You Know My Emotion? Emotion-Aware Strategy Recognition towards a Persuasive Dialogue System24 Jun 2022
- 2021Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling7 Jul 2021
- 2021DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues2 Jun 2021