  We address the task of sentence retrieval for open-ended dialogues. The goal
is to retrieve sentences from a document corpus that contain information useful
for generating the next turn in a given dialogue. Prior work on dialogue-based
retrieval focused on specific types of dialogues: either conversational QA or
conversational search. To address a broader scope of this task where any type
of dialogue can be used, we constructed a dataset that includes open-ended
dialogues from Reddit, candidate sentences from Wikipedia for each dialogue and
human annotations for the sentences. We report the performance of several
retrieval baselines, including neural retrieval models, over the dataset. To
adapt neural models to the types of dialogues in the dataset, we explored an
approach to induce a large-scale weakly supervised training data from Reddit.
Using this training set significantly improved the performance over training on
the MS MARCO dataset.
