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SimLab: A Platform for Simulation-based Evaluation of Conversational Information Access Systems

Nolwenn Bernard, Sharath Chandra Etagi Suresh, Krisztian Balog, ChengXiang Zhai

TL;DR

SimLab addresses the persistent challenge of evaluating conversational information access systems with reproducible experiments by introducing a cloud-based platform for simulation-based evaluation of CIA agents and user simulators. The platform combines an online Evaluation Framework, containerized systems, a Systems Registry, VM management, and monitoring within a cloud-native architecture, demonstrated through an initial conversational movie recommendation use case with a public leaderboard. Key contributions include specifying platform requirements, detailing implementation choices (Python-based framework, Flask/React web app, MongoDB, Docker registry, Jenkins, Grafana/Prometheus), and analyzing costs on GCP. The work envisions accelerating research, enhancing reproducibility, and supporting education, while inviting community participation to build a self-sustaining ecosystem for CIA and user simulation research.

Abstract

Progress in conversational information access (CIA) systems has been hindered by the difficulty of evaluating such systems with reproducible experiments. While user simulation offers a promising solution, the lack of infrastructure and tooling to support this evaluation paradigm remains a significant barrier. To address this gap, we introduce SimLab, the first cloud-based platform providing a centralized solution for the community to benchmark both conversational systems and user simulators in a controlled and reproducible setting. We articulate the requirements for such a platform and propose a general infrastructure to meet them. We then present the design and implementation of an initial version of SimLab and showcase its features through an initial simulation-based evaluation task in conversational movie recommendation. Furthermore, we discuss the platform's sustainability and future opportunities for development, inviting the community to drive further progress in the fields of CIA and user simulation.

SimLab: A Platform for Simulation-based Evaluation of Conversational Information Access Systems

TL;DR

SimLab addresses the persistent challenge of evaluating conversational information access systems with reproducible experiments by introducing a cloud-based platform for simulation-based evaluation of CIA agents and user simulators. The platform combines an online Evaluation Framework, containerized systems, a Systems Registry, VM management, and monitoring within a cloud-native architecture, demonstrated through an initial conversational movie recommendation use case with a public leaderboard. Key contributions include specifying platform requirements, detailing implementation choices (Python-based framework, Flask/React web app, MongoDB, Docker registry, Jenkins, Grafana/Prometheus), and analyzing costs on GCP. The work envisions accelerating research, enhancing reproducibility, and supporting education, while inviting community participation to build a self-sustaining ecosystem for CIA and user simulation research.

Abstract

Progress in conversational information access (CIA) systems has been hindered by the difficulty of evaluating such systems with reproducible experiments. While user simulation offers a promising solution, the lack of infrastructure and tooling to support this evaluation paradigm remains a significant barrier. To address this gap, we introduce SimLab, the first cloud-based platform providing a centralized solution for the community to benchmark both conversational systems and user simulators in a controlled and reproducible setting. We articulate the requirements for such a platform and propose a general infrastructure to meet them. We then present the design and implementation of an initial version of SimLab and showcase its features through an initial simulation-based evaluation task in conversational movie recommendation. Furthermore, we discuss the platform's sustainability and future opportunities for development, inviting the community to drive further progress in the fields of CIA and user simulation.

Paper Structure

This paper contains 29 sections, 4 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Background
  3. Traditional Evaluation Methods
  4. Simulation-based Evaluation
  5. Evaluation-as-a-Service
  6. SimLab
  7. Platform Requirements
  8. The SimLab Platform
  9. Online Evaluation Support (R1)
  10. Flexibility (R2)
  11. Scalability and Portability (R3)
  12. Intuitive Use (R4)
  13. Extensibility (R5)
  14. Implementation and Deployment
  15. Evaluation Framework
  16. ...and 14 more sections

Figures (4)

  • Figure 1: Vision for SimLab including the different stakeholders and resources involved in the simulation-based evaluation of conversational agents. The straight blue arrows represent the submissions of conversational agents and user simulators, while the dashed blue arrows represent access to the results.
  • Figure 2: Overview of the SimLab platform. Purple and blue arrows represent data and system flow respectively, while the green arrows indicate contributions to the platform by maintainers and developers. Grey boxes denote the components implemented by us.
  • Figure 3: UML activity diagram of the simulation-based evaluation process. The experiment data, highlighted in green boxes, is saved in the Storage. It is assumed that the systems are available in the Systems Registry.
  • Figure 4: Leaderboard page for the movie recommendation task. The results for two runs are placed in a table below the "Download results" button.