works on

From the 1 of 27 linked papers with an AI index.

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20162023
most citedREALM: Retrieval-Augmented Language Model Pre-Training

521 citations · 1.6k across the 20 of their papers we have counts for

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Showing 2018 · cs.CLShow all

7 papers · 2 filters

cs.CL2018★ 1 cited

Improving Span-based Question Answering Systems with Coarsely Labeled Data

Hao Cheng, Ming-Wei Chang, Kenton Lee +3

We study approaches to improve fine-grained short answer Question Answering models by integrating coarse-grained data annotated for paragraph-level relevance and show that coarsely…

cs.CL2018

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Jacob Devlin, Ming-Wei Chang, Kenton Lee +1

We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers. Unlike recent language representation models…

cs.CL2018★ 7 cited

Syntactic Scaffolds for Semantic Structures

Swabha Swayamdipta, Sam Thomson, Kenton Lee +3

We introduce the syntactic scaffold, an approach to incorporating syntactic information into semantic tasks. Syntactic scaffolds avoid expensive syntactic processing at runtime, on…

cs.CL2018★ 1 cited

Long Short-Term Memory as a Dynamically Computed Element-wise Weighted Sum

Omer Levy, Kenton Lee, Nicholas FitzGerald +1

LSTMs were introduced to combat vanishing gradients in simple RNNs by augmenting them with gated additive recurrent connections. We present an alternative view to explain the succe…

cs.CL2018★ 15 cited

Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling

Luheng He, Kenton Lee, Omer Levy +1

Recent BIO-tagging-based neural semantic role labeling models are very high performing, but assume gold predicates as part of the input and cannot incorporate span-level features.…

cs.CL2018

Higher-order Coreference Resolution with Coarse-to-fine Inference

Kenton Lee, Luheng He, Luke Zettlemoyer

We introduce a fully differentiable approximation to higher-order inference for coreference resolution. Our approach uses the antecedent distribution from a span-ranking architectu…