# ParlAI: A Dialog Research Software Platform

## TL;DR

ParlAI is an open-source platform that unifies dialog research tasks, models, and data, facilitating easier development, comparison, and evaluation of dialog systems across multiple datasets and models.

## Contribution

It introduces a comprehensive, unified platform for dialog research that supports diverse datasets, models, and evaluation methods in a single framework.

## Key findings

- Supports over 20 dialog tasks and datasets.
- Includes multiple neural dialog models for benchmarking.
- Enables integration with human evaluation and reinforcement learning.

## Abstract

We introduce ParlAI (pronounced "par-lay"), an open-source software platform for dialog research implemented in Python, available at http://parl.ai. Its goal is to provide a unified framework for sharing, training and testing of dialog models, integration of Amazon Mechanical Turk for data collection, human evaluation, and online/reinforcement learning; and a repository of machine learning models for comparing with others' models, and improving upon existing architectures. Over 20 tasks are supported in the first release, including popular datasets such as SQuAD, bAbI tasks, MCTest, WikiQA, QACNN, QADailyMail, CBT, bAbI Dialog, Ubuntu, OpenSubtitles and VQA. Several models are integrated, including neural models such as memory networks, seq2seq and attentive LSTMs.