The TREC Conversational Assistance Track (CAsT)

Conversational search benchmark at TREC

TREC Conversational Assistance Track (CAsT)

There are currently few datasets appropriate for training and evaluating models for Conversational Information Seeking (CIS). The main aim of TREC CAsT is to advance research on conversational search systems. The goal of the track is to create a reusable benchmark for open-domain information centric conversational dialogues.

The track will run in 2020 and establish a concrete and standard collection of data with information needs to make systems directly comparable.

This is the second year of TREC CAsT, which will run as a track in TREC. This year we aim to focus on candidate information ranking in context:

Year 2 (TREC 2020)

Data

Topics

Collection

News

Contact

Important Dates

Organizers

Year 1 (TREC 2019)

2019 Data

Topics

Resolved Topic Annotations

Baselines

Collection

Document ID format

Duplicate handling

Code and tools