Adapting to the Long Tail: A Meta-Analysis of Transfer Learning Research for Language Understanding Tasks.

Natural language understanding (NLU) has made massive progress driven by large benchmarks, but benchmarks often leave a long tail of infrequent phenomena underrepresented. We reflect on the question: We conceptualize the long tail using macro-level dimensions (underrepresented genres, topics, etc.), and perform a qualitative meta-analysis of 100 representative papers on transfer learning research for NLU.

Robust Knowledge Graph Completion with Stacked Convolutions and a Student Re-Ranking Network.

Knowledge Graph (KG) completion research usually focuses on densely connected benchmark datasets that are not representative of real KGs. We curate two KG datasets that include biomedical and encyclopedic knowledge and use an existing commonsense KG dataset to explore KG completion in the more realistic setting where dense connectivity is not guaranteed. We develop a deep convolutional network that utilizes textual entity representations and demonstrate that our model outperforms recent KG completion methods in this challenging setting.

Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research.

Natural language processing (NLP) research combines the study of universal principles, through basic science, with applied science targeting specific use cases and settings. However, the process of exchange between basic NLP and applications is often assumed to emerge naturally, resulting in many innovations going unapplied and many important questions left unstudied. We describe a new paradigm of , which aims to structure and facilitate the processes by which basic and applied NLP research inform one another.

Are children with autism more responsive to animated characters? A study of interactions with humans and human-controlled avatars.

Few direct comparisons have been made between the responsiveness of children with autism to computer-generated or animated characters and their responsiveness to humans. Twelve 4- to 8-year-old children with autism interacted with a human therapist; a human-controlled, interactive avatar in a theme park; a human actor speaking like the avatar; and cartoon characters who sought social responses. We found superior gestural and verbal responses to the therapist; intermediate response levels to the avatar and the actor; and poorest responses to the cartoon characters, although attention was equivalent across conditions.

Is he being bad? Social and language brain networks during social judgment in children with autism.

Individuals with autism often violate social rules and have lower accuracy in identifying and explaining inappropriate social behavior. Twelve children with autism (AD) and thirteen children with typical development (TD) participated in this fMRI study of the neurofunctional basis of social judgment. Participants indicated in which of two pictures a boy was being bad (Social condition) or which of two pictures was outdoors (Physical condition).