2 citations · 2 across the 3 of their papers we have counts for
10 papers
POQue: Asking Participant-specific Outcome Questions for a Deeper Understanding of Complex Events
Sai Vallurupalli, Sayontan Ghosh, Katrin Erk +2
Knowledge about outcomes is critical for complex event understanding but is hard to acquire. We show that by pre-identifying a participant in a complex event, crowd workers are abl…
Transferring Semantic Knowledge Into Language Encoders
Mohammad Umair, Francis Ferraro
We introduce semantic form mid-tuning, an approach for transferring semantic knowledge from semantic meaning representations into transformer-based language encoders. In mid-tuning…
Learning a Reversible Embedding Mapping using Bi-Directional Manifold Alignment
Ashwinkumar Ganesan, Francis Ferraro, Tim Oates
We propose a Bi-Directional Manifold Alignment (BDMA) that learns a non-linear mapping between two manifolds by explicitly training it to be bijective. We demonstrate BDMA by train…
A Discrete Variational Recurrent Topic Model without the Reparametrization Trick
Mehdi Rezaee, Francis Ferraro
We show how to learn a neural topic model with discrete random variables---one that explicitly models each word's assigned topic---using neural variational inference that does not…
On the Complementary Nature of Knowledge Graph Embedding, Fine Grain Entity Types, and Language Modeling
Rajat Patel, Francis Ferraro
We demonstrate the complementary natures of neural knowledge graph embedding, fine-grain entity type prediction, and neural language modeling. We show that a language model-inspire…
Event Representation with Sequential, Semi-Supervised Discrete Variables
Mehdi Rezaee, Francis Ferraro
Within the context of event modeling and understanding, we propose a new method for neural sequence modeling that takes partially-observed sequences of discrete, external knowledge…