b'Kenton Lee'

research

∙ 05/31/2023

From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces

Much of the previous work towards digital agents for graphical user inte...

0 Peter Shaw, et al. ∙

research

∙ 05/23/2023

Anchor Prediction: Automatic Refinement of Internet Links

Internet links enable users to deepen their understanding of a topic by ...

0 Nelson F. Liu, et al. ∙

research

∙ 05/19/2023

QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operations

Formulating selective information needs results in queries that implicit...

0 Chaitanya Malaviya, et al. ∙

research

∙ 04/11/2023

Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference

We propose Conditional Adapter (CoDA), a parameter-efficient transfer le...

0 Tao Lei, et al. ∙

research

∙ 02/22/2023

Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entities

Large-scale multi-modal pre-training models such as CLIP and PaLI exhibi...

0 Hexiang Hu, et al. ∙

research

∙ 04/02/2022

Generating recommendations for entity-oriented exploratory search

We introduce the task of recommendation set generation for entity-orient...

0 David Wadden, et al. ∙

research

∙ 06/30/2021

Revisiting the Primacy of English in Zero-shot Cross-lingual Transfer

Despite their success, large pre-trained multilingual models have not co...

0 Iulia Turc, et al. ∙

research

∙ 04/17/2021

Joint Passage Ranking for Diverse Multi-Answer Retrieval

We study multi-answer retrieval, an under-explored problem that requires...

0 Sewon Min, et al. ∙

research

∙ 02/02/2021

Neural Data Augmentation via Example Extrapolation

In many applications of machine learning, certain categories of examples...

0 Kenton Lee, et al. ∙

research

∙ 01/01/2021

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

We review the EfficientQA competition from NeurIPS 2020. The competition...

15 Sewon Min, et al. ∙

research

∙ 11/09/2020

CapWAP: Captioning with a Purpose

The traditional image captioning task uses generic reference captions to...

1 Adam Fisch, et al. ∙

research

∙ 10/22/2020

XOR QA: Cross-lingual Open-Retrieval Question Answering

Multilingual question answering tasks typically assume answers exist in ...

9 Akari Asai, et al. ∙

research

∙ 05/05/2020

Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering

We address the problem of extractive question answering using document-l...

0 Hao Cheng, et al. ∙

research

∙ 04/24/2020

Contextualized Representations Using Textual Encyclopedic Knowledge

We present a method to represent input texts by contextualizing them joi...

0 Mandar Joshi, et al. ∙

research

∙ 02/10/2020

REALM: Retrieval-Augmented Language Model Pre-Training

Language model pre-training has been shown to capture a surprising amoun...

0 Kelvin Guu, et al. ∙

research

∙ 08/31/2019

Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehension

Reading comprehension models have been successfully applied to extractiv...

0 Daniel Andor, et al. ∙

research

∙ 08/23/2019

Well-Read Students Learn Better: The Impact of Student Initialization on Knowledge Distillation

Recent developments in NLP have been accompanied by large, expensive mod...

0 Iulia Turc, et al. ∙

research

∙ 06/18/2019

Zero-Shot Entity Linking by Reading Entity Descriptions

We present the zero-shot entity linking task, where mentions must be lin...

0 Lajanugen Logeswaran, et al. ∙

research

∙ 06/01/2019

Latent Retrieval for Weakly Supervised Open Domain Question Answering

Recent work on open domain question answering (QA) assumes strong superv...

0 Kenton Lee, et al. ∙

research

∙ 05/24/2019

BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

In this paper we study yes/no questions that are naturally occurring ---...

0 Christopher Clark, et al. ∙

research

∙ 01/26/2019

Language Model Pre-training for Hierarchical Document Representations

Hierarchical neural architectures are often used to capture long-distanc...

0 Ming-Wei Chang, et al. ∙

research

∙ 01/24/2019

A BERT Baseline for the Natural Questions

This technical note describes a new baseline for the Natural Questions. ...

0 Chris Alberti, et al. ∙

research

∙ 11/05/2018

Improving Span-based Question Answering Systems with Coarsely Labeled Data

We study approaches to improve fine-grained short answer Question Answer...

0 Hao Cheng, et al. ∙

research

∙ 10/11/2018

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

We introduce a new language representation model called BERT, which stan...

0 Jacob Devlin, et al. ∙

research

∙ 08/30/2018

Syntactic Scaffolds for Semantic Structures

We introduce the syntactic scaffold, an approach to incorporating syntac...

0 Swabha Swayamdipta, et al. ∙

research

∙ 05/12/2018

Jointly Predicting Predicates and Arguments in Neural Semantic Role Labeling

Recent BIO-tagging-based neural semantic role labeling models are very h...

0 Luheng He, et al. ∙

research

∙ 05/09/2018

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

LSTMs were introduced to combat vanishing gradients in simple RNNs by au...

4 Omer Levy, et al. ∙

research

∙ 04/15/2018

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

We introduce a fully differentiable approximation to higher-order infere...

0 Kenton Lee, et al. ∙

research

∙ 02/15/2018

Deep contextualized word representations

We introduce a new type of deep contextualized word representation that ...

0 Matthew E. Peters, et al. ∙

research

∙ 07/21/2017

End-to-end Neural Coreference Resolution

We introduce the first end-to-end coreference resolution model and show ...

0 Kenton Lee, et al. ∙

research

∙ 05/21/2017

Recurrent Additive Networks

We introduce recurrent additive networks (RANs), a new gated RNN which i...

0 Kenton Lee, et al. ∙

research

∙ 11/04/2016

Learning Recurrent Span Representations for Extractive Question Answering

The reading comprehension task, that asks questions about a given eviden...

0 Kenton Lee, et al. ∙

research

∙ 07/05/2016

Global Neural CCG Parsing with Optimality Guarantees

We introduce the first global recursive neural parsing model with optima...

0 Kenton Lee, et al. ∙

Kenton Lee

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