Before revision:  In this paper, we propose to benchmark coherence models on a number of synthetic and downstream tasks. In particular, we evaluate well-known traditional and neural coherence models on  sentence ordering tasks, and also on three downstream applications including coherence evaluation for machine translation, summarization and next utterance prediction .
After revision:  However, coherence models are typically evaluated only on synthetic tasks, which may not be representative of their performance in downstream applications. To investigate how representative the synthetic tasks are of downstream use cases, we conduct experiments on benchmarking well-known traditional and neural coherence models on sentence ordering tasks, and also on three downstream applications including coherence evaluation for machine translation, summarization and next utterance prediction .