4 citations · 4 across the 2 of their papers we have counts for
5 papers
Visually Grounded Continual Learning of Compositional Phrases
Xisen Jin, Junyi Du, Arka Sadhu +2
Humans acquire language continually with much more limited access to data samples at a time, as compared to contemporary NLP systems. To study this human-like language acquisition…
A Benchmark for Structured Procedural Knowledge Extraction from Cooking Videos
Frank F. Xu, Lei Ji, Botian Shi +4
Watching instructional videos are often used to learn about procedures. Video captioning is one way of automatically collecting such knowledge. However, it provides only an indirec…
Improving BERT Fine-tuning with Embedding Normalization
Wenxuan Zhou, Junyi Du, Xiang Ren
Large pre-trained sentence encoders like BERT start a new chapter in natural language processing. A common practice to apply pre-trained BERT to sequence classification tasks (e.g.…
NERO: A Neural Rule Grounding Framework for Label-Efficient Relation Extraction
Wenxuan Zhou, Hongtao Lin, Bill Yuchen Lin +4
Deep neural models for relation extraction tend to be less reliable when perfectly labeled data is limited, despite their success in label-sufficient scenarios. Instead of seeking…
Eliciting Knowledge from Experts:Automatic Transcript Parsing for Cognitive Task Analysis
Junyi Du, He Jiang, Jiaming Shen +1
Cognitive task analysis (CTA) is a type of analysis in applied psychology aimed at eliciting and representing the knowledge and thought processes of domain experts. In CTA, often h…