arXiv subjects

Sharath Chandra Etagi Suresh

Publications and source records attributed to Sharath Chandra Etagi Suresh.

2 recordsLinked to original sources

arXiv2025

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

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.

cs.IR↗

arXiv2023

Social Commonsense-Guided Search Query Generation for Open-Domain Knowledge-Powered Conversations

Open-domain dialog involves generating search queries that help obtain relevant knowledge for holding informative conversations. However, it can be challenging to determine what information to retrieve when the user is passive and does not express a clear need or request. To tackle this issue, we present a novel approach that focuses on generating internet search queries that are guided by social commonsense. Specifically, we leverage a commonsense dialog system to establish connections related to the conversation topic, which subsequently guides our query generation. Our proposed framework addresses passive user interactions by integrating topic tracking, commonsense response generation and instruction-driven query generation. Through extensive evaluations, we show that our approach overcomes limitations of existing query generation techniques that rely solely on explicit dialog information, and produces search queries that are more relevant, specific, and compelling, ultimately resulting in more engaging responses.

cs.CL↗