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07/19/2023
Efficiency Pentathlon: A Standardized Arena for Efficiency Evaluation
Rising computational demands of modern natural language processing (NLP)...
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06/30/2023
Queer People are People First: Deconstructing Sexual Identity Stereotypes in Large Language Models
Large Language Models (LLMs) are trained primarily on minimally processe...
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06/29/2023
Surveying (Dis)Parities and Concerns of Compute Hungry NLP Research
Many recent improvements in NLP stem from the development and use of lar...
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05/24/2023
Large Language Model Distillation Doesn't Need a Teacher
Knowledge distillation trains a smaller student model to match the outpu...
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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 ...
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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...
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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...
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12/19/2022
DSI++: Updating Transformer Memory with New Documents
Differentiable Search Indices (DSIs) encode a corpus of documents in the...
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12/11/2022
Error-aware Quantization through Noise Tempering
Quantization has become a predominant approach for model compression, en...
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11/08/2022
Bridging Fairness and Environmental Sustainability in Natural Language Processing
Fairness and environmental impact are important research directions for ...
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10/14/2022
Mention Annotations Alone Enable Efficient Domain Adaptation for Coreference Resolution
Although, recent advances in neural network models for coreference resol...
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10/13/2022
SQuAT: Sharpness- and Quantization-Aware Training for BERT
Quantization is an effective technique to reduce memory footprint, infer...
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06/10/2022
Measuring the Carbon Intensity of AI in Cloud Instances
By providing unprecedented access to computational resources, cloud comp...
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05/25/2022
Train Flat, Then Compress: Sharpness-Aware Minimization Learns More Compressible Models
Model compression by way of parameter pruning, quantization, or distilla...
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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...
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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...
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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...
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06/05/2019
Energy and Policy Considerations for Deep Learning in NLP
Recent progress in hardware and methodology for training neural networks...
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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...
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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...
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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...
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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...
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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...
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11/18/2017
Automatically Extracting Action Graphs from Materials Science Synthesis Procedures
Computational synthesis planning approaches have achieved recent success...
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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...
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05/01/2017
Dependency Parsing with Dilated Iterated Graph CNNs
Dependency parses are an effective way to inject linguistic knowledge in...
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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-...
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11/19/2015
Multilingual Relation Extraction using Compositional Universal Schema
Universal schema builds a knowledge base (KB) of entities and relations ...
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10/30/2014
