activity
20192025
most citedLagging Inference Networks and Posterior Collapse in Variational Autoencoders

128 citations · 135 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2025

Victim as a Service: Designing a System for Engaging with Interactive Scammers

Daniel Spokoyny, Nikolai Vogler, Xin Gao +7

Pig butchering, and similar interactive online scams, lower their victims' defenses by building trust over extended periods of conversation - sometimes weeks or months. They have b…

cs.CL2023★ 5 cited

Towards Answering Climate Questionnaires from Unstructured Climate Reports

Daniel Spokoyny, Tanmay Laud, Tom Corringham +1

The topic of Climate Change (CC) has received limited attention in NLP despite its urgency. Activists and policymakers need NLP tools to effectively process the vast and rapidly gr…

cs.CL2021

Masked Measurement Prediction: Learning to Jointly Predict Quantities and Units from Textual Context

Daniel Spokoyny, Ivan Lee, Zhao Jin +1

Physical measurements constitute a large portion of numbers in academic papers, engineering reports, and web tables. Current benchmarks fall short of properly evaluating numeracy o…

cs.CL2020★ 2 cited

An Empirical Investigation of Contextualized Number Prediction

Daniel Spokoyny, Taylor Berg-Kirkpatrick

We conduct a large scale empirical investigation of contextualized number prediction in running text. Specifically, we consider two tasks: (1)masked number prediction-predicting a…

cs.LG2019★ 128 cited

Lagging Inference Networks and Posterior Collapse in Variational Autoencoders

Junxian He, Daniel Spokoyny, Graham Neubig +1

The variational autoencoder (VAE) is a popular combination of deep latent variable model and accompanying variational learning technique. By using a neural inference network to app…