22 citations · 22 across the 2 of their papers we have counts for
4 papers
KEMP: Keyframe-Based Hierarchical End-to-End Deep Model for Long-Term Trajectory Prediction
Qiujing Lu, Weiqiao Han, Jeffrey Ling +4
Predicting future trajectories of road agents is a critical task for autonomous driving. Recent goal-based trajectory prediction methods, such as DenseTNT and PECNet, have shown go…
Learning Cross-Context Entity Representations from Text
Jeffrey Ling, Nicholas FitzGerald, Zifei Shan +4
Language modeling tasks, in which words, or word-pieces, are predicted on the basis of a local context, have been very effective for learning word embeddings and context dependent…
Fusion of Detected Objects in Text for Visual Question Answering
Chris Alberti, Jeffrey Ling, Michael Collins +1
To advance models of multimodal context, we introduce a simple yet powerful neural architecture for data that combines vision and natural language. The "Bounding Boxes in Text Tran…
Matching the Blanks: Distributional Similarity for Relation Learning
Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling +1
General purpose relation extractors, which can model arbitrary relations, are a core aspiration in information extraction. Efforts have been made to build general purpose extractor…