Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

34 papers
Sakura: Large-scale Incorrect Example Retrieval System for Learners of Japanese as a Second Language (P19-3)

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Challenge: Existing example retrieval systems do not include grammatically incorrect examples . existing systems only provide a small number of examples, hence, learners cannot acquire sufficient information when they search .
Approach: They propose an incorrect example retrieval system called Sakura using a large-scale dataset for Japanese language learners.
Outcome: The proposed system is more useful than previous systems.
SLATE: A Super-Lightweight Annotation Tool for Experts (P19-3)

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Challenge: a new annotation tool is designed to fill the niche of a lightweight interface for terminal users . current tools are built with direct manipulation via a Graphical User Interface (GUI) this approach is time-consuming and difficult to modify .
Approach: They propose a terminal-based annotation tool that supports multiple annotations . they use a text-based interface that uses almost the entire screen to display documents .
Outcome: The proposed tool is designed to fill the niche of a lightweight interface for users with a terminal-based workflow.
lingvis.io - A Linguistic Visual Analytics Framework (P19-3)

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Challenge: Using a modular framework, linguistic visual analytics applications can be rapidly prototypized using a web-based framework.
Approach: They propose a modular framework for rapid prototyping of linguistic, web-based, visual analytics applications.
Outcome: The proposed framework supports rapid prototyping of linguistic, web-based, visual analytics applications.
SARAL: A Low-Resource Cross-Lingual Domain-Focused Information Retrieval System for Effective Rapid Document Triage (P19-3)

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Challenge: a new cross-lingual information retrieval system for low-resource languages is available in less-frequently-taught languages . a multilingual system can search for relevant information in a haystack of documents in swahili or Somali . human-driven approaches to this problem are complicated in 'low-resourced' languages aaron sagar: "the key role played by humans in triaging results is complicated"
Approach: They propose an end-to-end cross-lingual information retrieval system for low-resource languages . the system enables English speakers to search foreign language repositories using English queries . it summarizes the retrieved documents in English with respect to a particular information need .
Outcome: The proposed system achieves top performance in the most recent IARPA MATERIAL CLIR+summarization evaluations.
Jiuge: A Human-Machine Collaborative Chinese Classical Poetry Generation System (P19-3)

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Challenge: Existing systems for automatic poetry generation are model-oriented, resulting in poor user participation.
Approach: They propose a human-machine collaborative Chinese classical poetry generation system called Jiuge . Jiuge allows users to revise unsatisfied parts of a generated poem draft repeatedly .
Outcome: The proposed system allows users to revise unsatisfied parts of a generated poem draft repeatedly.
Rapid Customization for Event Extraction (P19-3)

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Challenge: a novel system allows users to customize event extraction to find new event types and their arguments.
Approach: They propose a system that allows a user to find, expand and filter event triggers by exploring an unannotated development corpus.
Outcome: The proposed system can find, expand and filter event triggers from an unannotated development corpus . it trains a generic argument attachment model for extracting Actor, Place, and Time .
A Multiscale Visualization of Attention in the Transformer Model (P19-3)

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Challenge: Various tools have been developed to visualize attention in NLP models, ranging from attention-matrix heatmaps to bipartite graph representations.
Approach: They propose an open-source tool that visualizes attention at multiple scales and provides a unique perspective on the attention mechanism.
Outcome: The proposed model outperforms OpenAI GPT-2 and BERT on several language modeling benchmarks.
PostAc : A Visual Interactive Search, Exploration, and Analysis Platform for PhD Intensive Job Postings (P19-3)

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Challenge: Employers’ low awareness and interest in attracting PhD graduates means that the term “PhD” is rarely used as a keyword in job advertisements.
Approach: They propose an online platform that makes the job market visible to job seekers by analyzing the key factors that identify what an employer is looking for when they hire a highly skilled researcher.
Outcome: The proposed platform makes visible the geographic location, industry sector, job title, working hours, continuity, and wage of the research intensive jobs.
An adaptable task-oriented dialog system for stand-alone embedded devices (P19-3)

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Challenge: a proposed speech-based task-oriented dialogue system is built on a small embedded device . the system does not require internet connectivity because all components run locally on the device - a cost-effective solution .
Approach: They propose a spoken-language end-to-end task-oriented dialogue system for small embedded devices such as home appliances.
Outcome: The proposed system is based on a demo run offline on swiss raspberry pi . it eliminates privacy risks and eliminates server costs and latency .
AlpacaTag: An Active Learning-based Crowd Annotation Framework for Sequence Tagging (P19-3)

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Challenge: Existing sequence annotation tools focus on improving user interfaces and user interface.
Approach: They propose an open-source web-based data annotation framework for sequence tagging tasks . the framework is based on active learning and automatic crowd consolidation .
Outcome: The proposed framework is a comprehensive solution for sequence labeling tasks . it can be deployed in downstream systems while new annotations are being made .
ConvLab: Multi-Domain End-to-End Dialog System Platform (P19-3)

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Challenge: ConvLab is an open-source multi-domain end-to-end dialog system platform . it allows researchers to quickly set up experiments with reusable components and compare a large set of different approaches in common environments.
Approach: They propose to use an open-source multi-domain end-to-end dialog system platform to train and evaluate dialog bots in common environments.
Outcome: The proposed system enables researchers to quickly set up experiments with reusable components and compare a large set of different approaches in common environments.
Demonstration of a Neural Machine Translation System with Online Learning for Translators (P19-3)

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Challenge: a new method of "humanizing" automatic translations has been developed for the translation industry . a demonstration of an online learning system for machine translation in a production environment .
Approach: They present a system which implements online learning for neural machine translation in a production environment.
Outcome: The proposed system saves post-editing effort and adapts to a specific domain or user style.
FASTDial: Abstracting Dialogue Policies for Fast Development of Task Oriented Agents (P19-3)

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Challenge: Existing tools for creating task oriented dialogue agents are very flexible and require domain expertise to design them.
Approach: They propose a framework for task oriented dialogue agents built on top of the OpenDial toolkit.
Outcome: The proposed framework reduces programming effort and domain expert training time by hiding many implementation details.
A Neural, Interactive-predictive System for Multimodal Sequence to Sequence Tasks (P19-3)

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Challenge: a neural interactive-predictive system is used to tackle multimodal sequence to sequence tasks . it generates text predictions to different sequence to sequencing tasks, including machine translation, image and video captioning.
Approach: They present a neural interactive-predictive system for tackling multimodal sequence to sequence tasks.
Outcome: The proposed system reduces human effort during the correction process by providing alternative hypotheses.
NeuralClassifier: An Open-source Neural Hierarchical Multi-label Text Classification Toolkit (P19-3)

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Challenge: NeuralClassifier is a toolkit for hierarchical multi-label text classification.
Approach: They propose a toolkit for neural hierarchical multi-label text classification . they use a variety of text encoders to implement the model .
Outcome: The proposed model achieves comparable performance with reported results in the literature.
ADVISER: A Dialog System Framework for Education & Research (P19-3)

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Challenge: In this paper, we focus on task-oriented dialog systems, although our framework allows easy integration of non-task dialog systems and their combination.
Approach: They propose an open source dialog system framework for education and research that supports multi-domain task-oriented conversations in two languages.
Outcome: The proposed framework supports multi-domain task-oriented conversations in two languages and is open source for education and research.
KCAT: A Knowledge-Constraint Typing Annotation Tool (P19-3)

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Challenge: Recent years Natural Language Processing community has seen a surge of interest in fine-grained entity typing (FET) given an entity mention (i.e. a sequence of token spans representing an entity), FET aims at uncovering its contextdependent type.
Approach: They propose an efficient Knowledge Constraint Fine-grained Entity Typing Annotation Tool which further improves the entity typing process through entity linking together with some practical functions.
Outcome: The proposed tool improves the entity typing process by linking the candidate types with some practical functions.
An Environment for Relational Annotation of Political Debates (P19-3)

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Challenge: Scalable text analysis techniques can open corpora to new questions in computational social sciences and digital humanities.
Approach: They describe a tool that allows annotating newspaper text with rich information about claims (demands) raised by politicians and other actors.
Outcome: The MARDY tool realizes the complete workflow necessary for annotating a large newspaper text collection with rich information about claims (demands) raised by politicians and other actors.
GLTR: Statistical Detection and Visualization of Generated Text (P19-3)

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Challenge: GLTR is a tool to detect generated text that can be used by non-experts.
Approach: They propose a tool to detect generated text using a set of statistical methods that can be used by non-experts.
Outcome: The proposed method improves detection rate of fake text from 54% to 72% without training.
OpenKiwi: An Open Source Framework for Quality Estimation (P19-3)

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Challenge: Existing open-source frameworks for QE are based on complex ensemble systems, complicated architectures, or require not well-documented pretraining and fine-tuning of some components.
Approach: They introduce OpenKiwi, a Pytorch-based framework for translation quality estimation.
Outcome: The proposed framework performs state-of-the-art on word-level and sentence-level tasks and is near state-outperforming on sentence- and word-based tasks.
Microsoft Icecaps: An Open-Source Toolkit for Conversation Modeling (P19-3)

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Challenge: upcoming open-source natural language processing repository aims to train conversational agents for multi-turn situations.
Approach: They present the Intelligent Conversation Engine: Code and Pre-trained Systems (ICECAPS) the framework wraps TensorFlow functionality in a modular component-based architecture.
Outcome: The Intelligent Conversation Engine: Code and Pre-trained Systems (ICECAPS) is an open-source natural language processing repository.
PerspectroScope: A Window to the World of Diverse Perspectives (P19-3)

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Challenge: PerspectroScope is a web-based system that lets users query a discussion-worthy natural language claim .
Approach: They propose a web-based system which lets users query a discussion-worthy natural language claim and extract and visualize various perspectives in support or against the claim.
Outcome: The proposed system lets users query a discussion-worthy natural language claim and extract and visualize various perspectives in support or against the claim.
HEIDL: Learning Linguistic Expressions with Deep Learning and Human-in-the-Loop (P19-3)

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Challenge: HITL-ML approaches are too low-level and far-removed from human’s conceptual models.
Approach: They propose a prototype HITL-ML system that exposes the machine-learned model through high-level, explainable linguistic expressions formed of predicates representing semantic structure of text.
Outcome: The proposed system exposes the machine-learned model through high-level, explainable linguistic expressions formed of predicates representing semantic structure of text.
My Turn To Read: An Interleaved E-book Reading Tool for Developing and Struggling Readers (P19-3)

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Challenge: My Turn To Read is an educational app that helps struggling readers improve reading skills while reading for meaning and pleasure.
Approach: They propose an app that uses interleaved reading to help struggling readers improve reading skills while reading for meaning and pleasure.
Outcome: The app helps struggling readers improve reading skills while reading for meaning and pleasure.
GrapAL: Connecting the Dots in Scientific Literature (P19-3)

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Challenge: Several software tools are available to help researchers perform tasks such as searching for papers, assessing applicants for a research position and keeping track of papers published on topics of interest.
Approach: They introduce a graph database of academic literature with an intuitive schema and query language . they open source the demo code to help other researchers develop applications that build on it .
Outcome: The proposed tool can be used to find experts on a given topic for peer review, find indirect connections between biomedical entities, and compute citation-based metrics.
ClaimPortal: Integrated Monitoring, Searching, Checking, and Analytics of Factual Claims on Twitter (P19-3)

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Challenge: ClaimPortal is a web-based platform for monitoring, searching, checking and analyzing factual claims on Twitter from the American political domain.
Approach: They present a web-based platform for monitoring, searching, checking and analyzing English factual claims on Twitter from the American political domain.
Outcome: The proposed platform can monitor, search, check, and analyze English factual claims on Twitter from the political domain.
Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation (P19-3)

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Challenge: Texar is an open-source text generation toolkit that supports a broad set of text generation tasks.
Approach: They introduce Texar, an open-source text generation toolkit that supports text generation tasks.
Outcome: Texar supports machine translation, summarization, dialog, content manipulation, and more.
Parallax: Visualizing and Understanding the Semantics of Embedding Spaces via Algebraic Formulae (P19-3)

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Challenge: Embeddings are a fundamental component of many modern machine learning and natural language processing models.
Approach: They propose a tool for visualizing embedding spaces using parametric projections . they demonstrate the power of Parallax and propose % task-oriented approach .
Outcome: The proposed tool is based on two-dimensional projections without interpretable semantics . it enhances interpretability and allows for more fine-grained analysis .
Flambé: A Customizable Framework for Machine Learning Experiments (P19-3)

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Challenge: Flambé is a machine learning experimentation framework built to accelerate the entire research life cycle.
Approach: They propose a framework that allows users to write custom code but include that code as a component in a larger system.
Outcome: The proposed framework enables users to write custom code but include that code as a component in a larger system which is represented by a concise configuration file format.
A Modular Tool for Automatic Summarization (P19-3)

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Challenge: Abstractive automatic summarization methods are supervized, but they require large corpora to perform tasks.
Approach: They propose to use a modular tool for automatic summarization that is as simple as possible for end-users.
Outcome: The proposed tool is open source and written in Java . it could be used as a baseline for future work and evaluate methods on different corpora.
TARGER: Neural Argument Mining at Your Fingertips (P19-3)

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Challenge: Argumentation is a multi-disciplinary field that extends from philosophy and psychology to linguistics as well as to artificial intelligence.
Approach: They propose to use TARGER to tagging arguments in free text and keyword-based retrieval of arguments from a web-scale corpus.
Outcome: The proposed framework can be used without any reproducibility effort on the user's side and is easily portable to other domains and use cases.
MoNoise: A Multi-lingual and Easy-to-use Lexical Normalization Tool (P19-3)

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Challenge: In this paper, we demonstrate the online demo and command line interface of a lexical normalization system (MoNoise) for a variety of languages.
Approach: They propose to bundle seven datasets in six languages to form a new benchmark and a novel evaluation metric which is particularly suitable for cross-dataset comparisons.
Outcome: The proposed model is based on the original word and features from the original language for each normalization candidate.
Level-Up: Learning to Improve Proficiency Level of Essays (P19-3)

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Challenge: Many essays are submitted to tutoring services by English learners on the Web every day . few systems provide focused suggestions on how to raise the level of proficiency.
Approach: They propose a method for generating suggestions on a sentence for improving proficiency . they propose identifying grammatical elements and ranking related elements to provide suggestions .
Outcome: The proposed method helps english learners improve their writing and reading skills.
Learning to Link Grammar and Encyclopedic Information of Assist ESL Learners (P19-3)

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Challenge: Linggle Booster provides rich lexical information such as collocations and grammar patterns for target words.
Approach: They propose a system that takes an article, identifies target vocabulary, provides lexical information, and generates a quiz on target words.
Outcome: The proposed system has been evaluated on a set of target words and has a good performance.

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