Byeongchang Kim
Department of Computer Science and Engineering, Seoul National University, Seoul, Korea, SNU
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IEEE Conference on Computer Vision and Pattern…
We address personalization issues of image captioning, which have not been discussed yet in previous research. For a query image, we aim to generate a descriptive sentence, accounting for prior… Expand
We address the problem of abstractive summarization in two directions: proposing a novel dataset and a new model. First, we collect Reddit TIFU dataset, consisting of 120K posts from the online… Expand
We explore the problem of audio captioning1: generating natural language description for any kind of audio in the wild, which has been surprisingly unexplored in previous research. We contribute a… Expand
Knowledge-grounded dialogue is a task of generating an informative response based on both discourse context and external knowledge. As we focus on better modeling the knowledge selection in the… Expand
IEEE Transactions on Pattern Analysis and Machine…
We address personalized image captioning, which generates a descriptive sentence for a user's image, accounting for prior knowledge such as her active vocabulary or writing style in her previous… Expand
Although consistency has been a long-standing issue in dialogue agents, we show best-performing persona-conditioned generative models still suffer from high insensitivity to contradiction. Current… Expand