8 citations · 23 across the 5 of their papers we have counts for
5 papers
CommonsenseQA 2.0: Exposing the Limits of AI through Gamification
Alon Talmor, Ori Yoran, Ronan Le Bras +4
Constructing benchmarks that test the abilities of modern natural language understanding models is difficult - pre-trained language models exploit artifacts in benchmarks to achiev…
Symbolic Knowledge Distillation: from General Language Models to Commonsense Models
Peter West, Chandra Bhagavatula, Jack Hessel +6
The common practice for training commonsense models has gone from-human-to-corpus-to-machine: humans author commonsense knowledge graphs in order to train commonsense models. In th…
proScript: Partially Ordered Scripts Generation via Pre-trained Language Models
Keisuke Sakaguchi, Chandra Bhagavatula, Ronan Le Bras +3
Scripts - standardized event sequences describing typical everyday activities - have been shown to help understand narratives by providing expectations, resolving ambiguity, and fi…
Faster Than Real-time Facial Alignment: A 3D Spatial Transformer Network Approach in Unconstrained Poses
Chandrasekhar Bhagavatula, Chenchen Zhu, Khoa Luu +1
Facial alignment involves finding a set of landmark points on an image with a known semantic meaning. However, this semantic meaning of landmark points is often lost in 2D approach…
Towards a Deep Learning Framework for Unconstrained Face Detection
Yutong Zheng, Chenchen Zhu, Khoa Luu +3
Robust face detection is one of the most important pre-processing steps to support facial expression analysis, facial landmarking, face recognition, pose estimation, building of 3D…