b'Emma Strubell'

DeepAI AI Chat

Featured Co-authors

Zheng Wang
138 publications
Noah A. Smith
121 publications
Andrew McCallum
109 publications
Yi Tay
76 publications
Sameer Singh
73 publications
Florian Metze
72 publications
Stefanie Jegelka
64 publications
Mohit Iyyer
56 publications
Sarath Chandar
54 publications
Roy Schwartz
48 publications
Yonatan Bisk
46 publications

research

∙ 05/24/2023

Large Language Model Distillation Doesn't Need a Teacher

Knowledge distillation trains a smaller student model to match the outpu...

0 Ananya Harsh Jha, et al. ∙

research

∙ 04/29/2023

Regularizing Self-training for Unsupervised Domain Adaptation via Structural Constraints

Self-training based on pseudo-labels has emerged as a dominant approach ...

0 Rajshekhar Das, et al. ∙

research

∙ 02/13/2023

The Framework Tax: Disparities Between Inference Efficiency in Research and Deployment

Increased focus on the deployment of machine learning systems has led to...

0 Jared Fernandez, et al. ∙

research

∙ 12/20/2022

To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering

Recent advances in open-domain question answering (ODQA) have demonstrat...

0 Dheeru Dua, et al. ∙

research

∙ 12/19/2022

DSI++: Updating Transformer Memory with New Documents

Differentiable Search Indices (DSIs) encode a corpus of documents in the...

0 Sanket Vaibhav Mehta, et al. ∙

research

∙ 12/11/2022

Error-aware Quantization through Noise Tempering

Quantization has become a predominant approach for model compression, en...

0 Zheng Wang, et al. ∙

research

∙ 11/08/2022

Bridging Fairness and Environmental Sustainability in Natural Language Processing

Fairness and environmental impact are important research directions for ...

0 Marius Hessenthaler, et al. ∙

research

∙ 10/14/2022

Mention Annotations Alone Enable Efficient Domain Adaptation for Coreference Resolution

Although, recent advances in neural network models for coreference resol...

0 Nupoor Gandhi, et al. ∙

research

∙ 10/13/2022

SQuAT: Sharpness- and Quantization-Aware Training for BERT

Quantization is an effective technique to reduce memory footprint, infer...

0 Zheng Wang, et al. ∙

research

∙ 06/10/2022

Measuring the Carbon Intensity of AI in Cloud Instances

By providing unprecedented access to computational resources, cloud comp...

0 Jesse Dodge, et al. ∙

research

∙ 05/25/2022

Train Flat, Then Compress: Sharpness-Aware Minimization Learns More Compressible Models

Model compression by way of parameter pruning, quantization, or distilla...

0 Clara Na, et al. ∙

research

∙ 12/16/2021

An Empirical Investigation of the Role of Pre-training in Lifelong Learning

The lifelong learning paradigm in machine learning is an attractive alte...

5 Sanket Vaibhav Mehta, et al. ∙

research

∙ 10/16/2021

Improving Compositional Generalization with Self-Training for Data-to-Text Generation

Data-to-text generation focuses on generating fluent natural language re...

4 Sanket Vaibhav Mehta, et al. ∙

research

∙ 04/20/2021

WiFiMod: Transformer-based Indoor Human Mobility Modeling using Passive Sensing

Modeling human mobility has a wide range of applications from urban plan...

0 Amee Trivedi, et al. ∙

research

∙ 06/05/2019

Energy and Policy Considerations for Deep Learning in NLP

Recent progress in hardware and methodology for training neural networks...

0 Emma Strubell, et al. ∙

research

∙ 05/16/2019

The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures

Materials science literature contains millions of materials synthesis pr...

0 Sheshera Mysore, et al. ∙

research

∙ 12/31/2018

Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks

Leveraging new data sources is a key step in accelerating the pace of ma...

0 Edward Kim, et al. ∙

research

∙ 11/12/2018

Syntax Helps ELMo Understand Semantics: Is Syntax Still Relevant in a Deep Neural Architecture for SRL?

Do unsupervised methods for learning rich, contextualized token represen...

0 Emma Strubell, et al. ∙

research

∙ 04/23/2018

Linguistically-Informed Self-Attention for Semantic Role Labeling

The current state-of-the-art end-to-end semantic role labeling (SRL) mod...

0 Emma Strubell, et al. ∙

research

∙ 02/28/2018

Simultaneously Self-Attending to All Mentions for Full-Abstract Biological Relation Extraction

Most work in relation extraction forms a prediction by looking at a shor...

0 Patrick Verga, et al. ∙

research

∙ 11/18/2017

Automatically Extracting Action Graphs from Materials Science Synthesis Procedures

Computational synthesis planning approaches have achieved recent success...

0 Sheshera Mysore, et al. ∙

research

∙ 10/23/2017

Attending to All Mention Pairs for Full Abstract Biological Relation Extraction

Most work in relation extraction forms a prediction by looking at a shor...

0 Patrick Verga, et al. ∙

research

∙ 05/01/2017

Dependency Parsing with Dilated Iterated Graph CNNs

Dependency parses are an effective way to inject linguistic knowledge in...

0 Emma Strubell, et al. ∙

research

∙ 02/07/2017

Fast and Accurate Entity Recognition with Iterated Dilated Convolutions

Today when many practitioners run basic NLP on the entire web and large-...

0 Emma Strubell, et al. ∙

research

∙ 11/19/2015

Multilingual Relation Extraction using Compositional Universal Schema

Universal schema builds a knowledge base (KB) of entities and relations ...

0 Patrick Verga, et al. ∙

research

∙ 10/30/2014

Training for Fast Sequential Prediction Using Dynamic Feature Selection

We present paired learning and inference algorithms for significantly re...

0 Emma Strubell, et al. ∙