activity
20132026
most citedProbabilistic Frame Induction

87 citations · 140 across the 15 of their papers we have counts for

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Showing 2019Show all

9 papers · 1 filter

cs.CL20197 cited

Deconstructing and reconstructing word embedding algorithms

Edward Newell, Kian Kenyon-Dean, Jackie Chi Kit Cheung

Uncontextualized word embeddings are reliable feature representations of words used to obtain high quality results for various NLP applications. Given the historical success of wor…

cs.CL20199 cited

Can a Gorilla Ride a Camel? Learning Semantic Plausibility from Text

Ian Porada, Kaheer Suleman, Jackie Chi Kit Cheung

Modeling semantic plausibility requires commonsense knowledge about the world and has been used as a testbed for exploring various knowledge representations. Previous work has focu…

cs.LG2019

On Posterior Collapse and Encoder Feature Dispersion in Sequence VAEs

Teng Long, Yanshuai Cao, Jackie Chi Kit Cheung

Variational autoencoders (VAEs) hold great potential for modelling text, as they could in theory separate high-level semantic and syntactic properties from local regularities of na…

cs.CL2019

Countering the Effects of Lead Bias in News Summarization via Multi-Stage Training and Auxiliary Losses

Matt Grenander, Yue Dong, Jackie Chi Kit Cheung +1

Sentence position is a strong feature for news summarization, since the lead often (but not always) summarizes the key points of the article. In this paper, we show that recent neu…

cs.CL2019

Referring Expression Generation Using Entity Profiles

Meng Cao, Jackie Chi Kit Cheung

Referring Expression Generation (REG) is the task of generating contextually appropriate references to entities. A limitation of existing REG systems is that they rely on entity-sp…

cs.CL20193 cited

EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing

Yue Dong, Zichao Li, Mehdi Rezagholizadeh +1

We present the first sentence simplification model that learns explicit edit operations (ADD, DELETE, and KEEP) via a neural programmer-interpreter approach. Most current neural se…