ParlAI: A Dialog Research Software Platform
This platform addresses the need for a standardized and accessible tool for researchers in dialog AI, though it is incremental as it builds upon existing methods and datasets.
The authors introduced ParlAI, an open-source software platform for dialog research that provides a unified framework for sharing, training, and testing dialog models, integrating tools like Amazon Mechanical Turk, and offering a repository of models. The first release supports over 20 tasks, including popular datasets such as SQuAD, bAbI tasks, and Ubuntu, and integrates several neural models like memory networks and seq2seq.
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.