3 citations · 3 across the 1 of their papers we have counts for
3 papers · 1 filter
Meta Answering for Machine Reading
Benjamin Borschinger, Jordan Boyd-Graber, Christian Buck +7
We investigate a framework for machine reading, inspired by real world information-seeking problems, where a meta question answering system interacts with a black box environment.…
Zero-Shot Dual Machine Translation
Lierni Sestorain, Massimiliano Ciaramita, Christian Buck +1
Neural Machine Translation (NMT) systems rely on large amounts of parallel data. This is a major challenge for low-resource languages. Building on recent work on unsupervised and s…
Analyzing Language Learned by an Active Question Answering Agent
Christian Buck, Jannis Bulian, Massimiliano Ciaramita +4
We analyze the language learned by an agent trained with reinforcement learning as a component of the ActiveQA system [Buck et al., 2017]. In ActiveQA, question answering is framed…