Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

29 papers
OpenUE: An Open Toolkit of Universal Extraction from Text (2020.emnlp-demos)

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Challenge: a large number of natural language processing tasks focus on token-level or sentence-level understandings.
Approach: They propose an open-source and extensible toolkit for various extraction tasks . they deploy an online demo with restful APIs to support real-time extraction .
Outcome: The proposed model can be used to extract information from text without training and deployment.
BERTweet: A pre-trained language model for English Tweets (2020.emnlp-demos)

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Challenge: Experiments show that BERTweet outperforms strong baselines RoBERTa-base and XLM-R-base on three Tweet NLP tasks: Part-of-speech tagging, Named-entity recognition and text classification.
Approach: They propose to train a pre-trained language model for English Tweets using the RoBERTa pre training procedure and use it to train the model.
Outcome: Experiments show that the model outperforms baseline models on three Tweet NLP tasks: Part-of-speech tagging, Named-entity recognition and text classification.
NeuralQA: A Usable Library for Question Answering (Contextual Query Expansion + BERT) on Large Datasets (2020.emnlp-demos)

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Challenge: Existing tools for Question Answering (QA) have challenges that limit their use in practice.
Approach: They propose a library that integrates with existing infrastructure and offers helpful defaults for QA subtasks.
Outcome: NeuralQA integrates well with existing infrastructure and offers helpful defaults for QA subtasks.
Wikipedia2Vec: An Efficient Toolkit for Learning and Visualizing the Embeddings of Words and Entities from Wikipedia (2020.emnlp-demos)

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Challenge: Existing tools for learning the embeddings of words and entities from Wikipedia are not yet available.
Approach: They propose a Python-based tool for learning Wikipedia embeddings from Wikipedia . they use a Wikipedia dump file as an argument to issue a single command .
Outcome: The proposed tool achieves state-of-the-art results on the KORE entity relatedness dataset and competitive results on benchmark datasets.
ARES: A Reading Comprehension Ensembling Service (2020.emnlp-demos)

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Challenge: ARES is a machine reading comprehension (MRC) demonstration system which utilizes an ensemble of models to increase F1 by 2.3 points.
Approach: They propose a machine reading comprehension (MRC) demonstration system which utilizes an ensemble of models to increase F1 by 2.3 points.
Outcome: The proposed system increases F1 by 2.3 points on a short answer task using an ensemble of models.
Transformers: State-of-the-Art Natural Language Processing (2020.emnlp-demos)

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Challenge: Transformers is an open-source library that aims to open up advances in natural language processing to the wider machine learning community.
Approach: they propose an open-source library that aims to open up advances in machine learning to the wider community.
Outcome: Transformers is an open-source library with the goal of opening up these advances to the wider machine learning community.
AdapterHub: A Framework for Adapting Transformers (2020.emnlp-demos)

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Challenge: AdapterHub framework enables dynamic “stiching-in” of pre-trained adapters for different tasks and languages.
Approach: They propose a framework that allows dynamic "stiching-in" of pre-trained adapters for different tasks and languages.
Outcome: The proposed framework allows dynamic “stiching-in” of pre-trained adapters for different tasks and languages.
HUMAN: Hierarchical Universal Modular ANnotator (2020.emnlp-demos)

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Challenge: HUMAN is a web-based annotation tool that covers a variety of annotation tasks on textual and image data.
Approach: They propose a web-based annotation tool that covers a variety of annotation tasks on textual and image data.
Outcome: HUMAN covers a variety of annotation tasks on textual and image data and uses an internal deterministic state machine to chain different tasks in an interdependent manner.
DeezyMatch: A Flexible Deep Learning Approach to Fuzzy String Matching (2020.emnlp-demos)

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Challenge: DeezyMatch is a free, open-source software library written in Python for fuzzy string matching and candidate ranking.
Approach: They propose to use DeezyMatch to train new classifiers and fine-tune a pretrained model to generate rich vector representations from string inputs.
Outcome: The proposed algorithm can be used to find the best matching candidates in large knowledge bases and query sets.
CoSaTa: A Constraint Satisfaction Solver and Interpreted Language for Semi-Structured Tables of Sentences (2020.emnlp-demos)

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Challenge: Existing methods for inference using multiple facts are unable to combine more than two together.
Approach: They present an intuitive constraint satisfaction solver and interpreted language for knowledge bases of semi-structured tables expressed as text.
Outcome: The solver and interpreter are released as open source . the solver can express complex compositional "inference patterns"
InVeRo: Making Semantic Role Labeling Accessible with Intelligible Verbs and Roles (2020.emnlp-demos)

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Challenge: Semantic Role Labeling (SRL) is dependent on complex linguistic resources and sophisticated neural models, which makes the task difficult to approach for non-experts.
Approach: They propose a platform for semantic role labeling that provides verb sense and semantic role information with an easy to use Web interface and RESTful APIs.
Outcome: The proposed system provides human-readable verb sense and semantic role information with an easy to use Web interface and RESTful APIs.
Youling: an AI-assisted Lyrics Creation System (2020.emnlp-demos)

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Challenge: Recent studies have focused on a single pass of lyrics generation with little human intervention.
Approach: They propose an AI-assisted lyrics creation system that supports one pass full-text generation and interactive generation modes.
Outcome: The proposed system supports full-text generation and interactive generation modes . it also provides a revision module which enables users to revise undesired lyrics repeatedly.
A Technical Question Answering System with Transfer Learning (2020.emnlp-demos)

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Challenge: StackOverflow and AskUbuntu are popular open forum communities for technical question-answering, but it is expensive for human experts to provide timely and helpful responses.
Approach: They develop a system that automatically responds to questions from a siamese ALBERT network based on previously answered questions .
Outcome: The proposed system responds automatically to questions based on answers from previous users.
ENTYFI: A System for Fine-grained Entity Typing in Fictional Texts (2020.emnlp-demos)

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Challenge: ENTYFI is a web-based system for fine-grained typing of entity mentions in fictional texts.
Approach: They propose a web-based system for fine-grained typing of entity mentions in fictional texts . entity types are a core building block of current knowledge bases .
Outcome: The proposed system builds on 205 automatically induced high-quality type systems for popular fictional domains and provides recommendations towards reference type systems.
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models (2020.emnlp-demos)

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Challenge: Existing tools for modeling and understanding models are limited . existing tools can assist practitioners in understanding and evaluating models .
Approach: They present an open-source platform for visualization and understanding of NLP models.
Outcome: The language interpretability tool (lit) is an open-source platform for visualization and understanding of NLP models.
TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP (2020.emnlp-demos)

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Challenge: TextAttack provides implementations of 16 adversarial attacks from the literature and supports a variety of models and datasets.
Approach: They introduce a Python framework for adversarial attacks, data augmentation, and adversarially training in NLP.
Outcome: This paper introduces a Python framework for adversarial attacks, data augmentation, and adversarially training in NLP.
Easy, Reproducible and Quality-Controlled Data Collection with CROWDAQ (2020.emnlp-demos)

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Challenge: Efficient data collection is important for advancing research and building time-sensitive applications.
Approach: They propose an open-source platform that standardizes the data collection pipeline . it includes customizable user interface components, automated annotator qualification, and saved pipelines .
Outcome: The proposed platform simplifies data annotation significantly on diverse datasets . it can be used by researchers and engineers to improve reproducibility and minimize overhead .
SciSight: Combining faceted navigation and research group detection for COVID-19 exploratory scientific search (2020.emnlp-demos)

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Challenge: SciSight is a system for exploratory search of COVID-19 literature . it explores associations between biomedical facets extracted from papers .
Approach: They propose a system for exploratory search of COVID-19 literature that integrates two key capabilities: first, exploring associations between biomedical facets automatically extracted from papers; second, combining textual and network information to search and visualize groups of researchers and their ties.
Outcome: The proposed system has served over 15K users with over 42K page views and 13% returns.
SIMULEVAL: An Evaluation Toolkit for Simultaneous Translation (2020.emnlp-demos)

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Challenge: SimulEval is an evaluation toolkit for simultaneous text and speech translation.
Approach: They propose a server-client scheme for simultaneous translation that uses server input and client policies to evaluate models.
Outcome: The proposed evaluation toolkit is available for both text and speech translation.
Agent Assist through Conversation Analysis (2020.emnlp-demos)

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Challenge: Using conversational approach to information retrieval for agent assistance, customer support agents are a critical part of an organization's customer support team.
Approach: They propose a conversational approach to information retrieval for agent assistance that monitors an evolving conversation and recommends both responses and URLs of documents.
Outcome: The proposed system monitors an evolving conversation and recommends both responses and URLs of documents the agent can use in replies to their client.
NeuSpell: A Neural Spelling Correction Toolkit (2020.emnlp-demos)

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Challenge: a new spelling correction toolkit is available for free.
Approach: They propose an open-source toolkit for spelling correction in English . they train neural models using spelling errors in context and using richer contextual representations.
Outcome: The proposed spell-checker improves accuracy on synthetic examples and richer representations of the context.
LibKGE - A knowledge graph embedding library for reproducible research (2020.emnlp-demos)

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Challenge: Knowledge graph embedding models are trained to predict false triples and high scores for true triples.
Approach: LibKGE is an open-source PyTorch-based library for training, hyperparameter optimization, and evaluation of knowledge graph embedding models for link prediction.
Outcome: LibKGE provides implementations of common knowledge graph embedding models and training methods, and new ones can be easily added.
WantWords: An Open-source Online Reverse Dictionary System (2020.emnlp-demos)

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Challenge: Existing reverse dictionary systems only support English reverse dictionary queries . a reverse dictionary can help people who can't remember a word from memory .
Approach: They propose an online reverse dictionary system that outperforms other reverse dictionary systems . it supports Chinese and English-Chinese as well as Chinese-English cross-lingual reverse dictionary queries .
Outcome: The proposed reverse dictionary outperforms other reverse dictionary systems on performance . it supports Chinese and English-Chinese as well as Chinese-English queries .
BENNERD: A Neural Named Entity Linking System for COVID-19 (2020.emnlp-demos)

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Challenge: a biomedical entity linking system is available for COVID-19 research.
Approach: They propose a biomedical entity linking system that detects named enti- ties in text and links them to the UMLS knowledge base.
Outcome: The proposed system detects named enti- ties in text and links them to the unified medical language system (UMS) knowledge base entries.
RoFT: A Tool for Evaluating Human Detection of Machine-Generated Text (2020.emnlp-demos)

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Challenge: Existing studies on how humans perceive machine-generated text are limited due to the prohibitive cost of running human evaluation studies.
Approach: They propose a task to detect the boundary at which a text passage starts off human-written transitions to being machine-generated.
Outcome: The proposed system evaluates machine-generated news articles on a wide range of domains.
A Data-Centric Framework for Composable NLP Workflows (2020.emnlp-demos)

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Challenge: Empirical natural language processing (NLP) systems involve interoperation among multiple components . a wealth of NLP toolkits exist ( 4), such as spaCy, DKPro, CoreNLP.
Approach: They propose a unified open-source framework that supports fast development of NLP workflows . framework includes processors for NLP tasks, visualization, and annotation .
Outcome: The framework offers processors for NLP tasks, visualization, and annotation, and is extensible . it is delivered through two modularized yet integratable open-source projects, Forte and Stave .
CoRefi: A Crowd Sourcing Suite for Coreference Annotation (2020.emnlp-demos)

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Challenge: Using a web-based coreference annotation suite, we demonstrate that non-expert annotators can be trained to perform and review coreference resolution tasks.
Approach: They propose a web-based coreference annotation suite oriented for crowdsourcing that provides guided onboarding and a novel algorithm for a reviewing phase.
Outcome: The proposed tool provides guided onboarding and a novel algorithm for a review phase.
Langsmith: An Interactive Academic Text Revision System (2020.emnlp-demos)

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Challenge: Currently, diversity and inclusion initiatives in the academic community are encouraged . however, writing papers in English can be a daunting task .
Approach: They propose a system that helps non-native English speakers to write papers in English . the system can suggest fluent, academic-style sentences based on their rough, incomplete phrases or sentences .
Outcome: The proposed system can help non-native English speakers write papers in English . the system can suggest fluent, academic-style sentences based on their rough sentences .
IsOBS: An Information System for Oracle Bone Script (2020.emnlp-demos)

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Challenge: Oracle bone script (OBS) documents are the oldest continuously-used writing system in the world and are important for linguistic and historical research.
Approach: They construct an information system for OBS to symbolize, serialize, and store OBS data at the character-level using efficient databases and retrieval modules.
Outcome: The proposed system symbolizes, serializes, and stores OBS data at the character-level, based on efficient databases and retrieval modules.

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