Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations
TexSmart: A System for Enhanced Natural Language Understanding (2021.acl-demo)
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Lemao Liu, Haisong Zhang, Haiyun Jiang, Yangming Li, Enbo Zhao, Kun Xu, Linfeng Song, Suncong Zheng, Botong Zhou, Dick Zhu, Xiao Feng, Tao Chen, Tao Yang, Dong Yu, Feng Zhang, ZhanHui Kang, Shuming Shi
| Challenge: | TexSmart supports fine-grained named entity recognition (NER) Large-scale fine-granular entity types are expected to provide richer semantic information for downstream NLP applications. |
| Approach: | They introduce TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities. |
| Outcome: | The proposed system supports fine-grained named entity recognition (NER) and enhanced semantic analysis functions. |
IntelliCAT: Intelligent Machine Translation Post-Editing with Quality Estimation and Translation Suggestion (2021.acl-demo)
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| Challenge: | Existing computer-aided translation tools require the translator to edit incorrect parts of a document, while ITP tools require fewer edits. |
| Approach: | They propose an interactive translation interface with neural models that streamline the post-editing process on machine translation output. |
| Outcome: | The proposed interface can significantly improve translation quality and a user study shows that it speeds up the post-editing process by 52.9% compared to translating from scratch. |
The Classical Language Toolkit: An NLP Framework for Pre-Modern Languages (2021.acl-demo)
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Kyle P. Johnson, Patrick J. Burns, John Stewart, Todd Cook, Clément Besnier, William J. B. Mattingly
| Challenge: | Classical Language Toolkit (CLTK) is an NLP framework for pre-modern languages . authors say it assumes pre-existing living languages, neglecting important characteristics of non-spoken historical languages despite their existence . |
| Approach: | The paper announces version 1.0 of the Classical Language Toolkit (CLTK) it is an NLP framework for pre-modern languages that uses assumptions specific to living languages . authors propose a modular processing pipeline that balances competing demands of algorithmic diversity with pre-configured defaults . |
| Outcome: | The Classical Language Toolkit (CLTK) is a new NLP framework for pre-modern languages . the framework is based on the existing frameworks and is available for almost 20 languages - including models . |
TextBox: A Unified, Modularized, and Extensible Framework for Text Generation (2021.acl-demo)
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Junyi Li, Tianyi Tang, Gaole He, Jinhao Jiang, Xiaoxuan Hu, Puzhao Xie, Zhipeng Chen, Zhuohao Yu, Wayne Xin Zhao, Ji-Rong Wen
| Challenge: | TextBox is an open-source text generation framework that is modularized and extensible. |
| Approach: | They propose to provide a unified, modularized, and extensible text generation framework that implements 21 text generation models on 9 benchmark datasets. |
| Outcome: | The proposed framework implements 21 models on 9 benchmark datasets and is available under the Apache License 2.0 license. |
Inside ASCENT: Exploring a Deep Commonsense Knowledge Base and its Usage in Question Answering (2021.acl-demo)
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| Challenge: | Structured knowledge bases (KBs) are a great way to explain and interpret outputs of systems leveraging the resources. |
| Approach: | They propose a web portal that allows users to understand its construction process and explore its content. |
| Outcome: | The proposed framework allows users to understand its construction process, explore its content, and observe its impact in the use case of question answering. |
SciConceptMiner: A system for large-scale scientific concept discovery (2021.acl-demo)
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| Challenge: | SciConceptMiner is a self-supervised system for the capture of scientific concepts . the system is scalable to the size of documents and the number of topics it can model . |
| Approach: | They propose a self-supervised system for the automatic capture of scientific concepts from academic publications and semi-structured data. |
| Outcome: | The proposed system achieves high accuracy (94.7%) with more than 740K scientific concepts. |
NeurST: Neural Speech Translation Toolkit (2021.acl-demo)
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| Challenge: | a toolkit for speech translation is available for free and provides step-by-step recipes for feature extraction, data preprocessing, distributed training, and evaluation. |
| Approach: | They propose to use NeurST to facilitate speech translation research for NLP researchers . they show experimental results for different benchmark datasets which can be regarded as reliable baselines . |
| Outcome: | The proposed framework provides reliable benchmarks for speech translation research. |
ParCourE: A Parallel Corpus Explorer for a Massively Multilingual Corpus (2021.acl-demo)
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| Challenge: | 7000 languages worldwide are spoken, but most research is focused on English . multilinguality is essential for multilingual research, and is a key component of the process. |
| Approach: | They propose a wordaligned parallel corpus that can be browsed using an online tool . they use the word alignment tools SimAlign and BabelNet to find the alignments . |
| Outcome: | The proposed tool can be set up for any parallel corpus and explores its quality and properties. |
MT-Telescope: An interactive platform for contrastive evaluation of MT systems (2021.acl-demo)
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| Challenge: | MT-Telescope is an open source, written in Python, and is built around a user friendly and dynamic web interface. |
| Approach: | They propose a platform to facilitate comparative analysis of the output quality of two Machine Translation (MT) systems. |
| Outcome: | The proposed platform supports fine-grained segment-level analysis and interactive visualisations that expose the fundamental differences in the performance of the compared systems. |
Supporting Complaints Investigation for Nursing and Midwifery Regulatory Agencies (2021.acl-demo)
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Piyawat Lertvittayakumjorn, Ivan Petej, Yang Gao, Yamuna Krishnamurthy, Anna Van Der Gaag, Robert Jago, Kostas Stathis
| Challenge: | Fig. 1 illustrates the major components and workflow of our proposed system to improve the efficiency of complaints investigation for nursing and midwifery regulators. |
| Approach: | They propose a decision support system that uses machine learning and natural language processing techniques to process complaints and predict their risk level. |
| Outcome: | The proposed system uses state-of-the-art machine learning and natural language processing techniques to process complaints and predict risk levels. |
CogIE: An Information Extraction Toolkit for Bridging Texts and CogNet (2021.acl-demo)
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| Challenge: | CogNet is a knowledge base that integrates three types of knowledge: linguistic knowledge, world knowledge and commonsense knowledge. |
| Approach: | They propose an information extraction toolkit called CogIE that is a bridge connecting raw texts and CogNet. |
| Outcome: | The proposed toolkit can ground raw texts to CogNet and leverage different types of knowledge to enrich extracted results. |
fastHan: A BERT-based Multi-Task Toolkit for Chinese NLP (2021.acl-demo)
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| Challenge: | Recently, the need for Chinese natural language processing (NLP) has a dramatic increase for many downstream applications. |
| Approach: | They propose to use Chinese word segmentation (CWS), Part-of-Speech (POS) tagging, named entity recognition (NER), and dependency parsing to train a multi-task model based on a pruned BERT. |
| Outcome: | The proposed model performs better than popular segmentation tools on a non-training corpus. |
Erase and Rewind: Manual Correction of NLP Output through a Web Interface (2021.acl-demo)
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| Challenge: | In the last years, NLP tools are being used in tasks such as textual inference, machine translation, hate speech detection. |
| Approach: | They propose an NLP annotation software that can be used to manually annotate texts and to fix mistakes in NLP pipelines. |
| Outcome: | The proposed tool can be used to manually annotate texts and fix errors in NLP pipelines, such as Stanford CoreNLP. |
ESRA: Explainable Scientific Research Assistant (2021.acl-demo)
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Pollawat Hongwimol, Peeranuth Kehasukcharoen, Pasit Laohawarutchai, Piyawat Lertvittayakumjorn, Aik Beng Ng, Zhangsheng Lai, Timothy Liu, Peerapon Vateekul
| Challenge: | Existing literature search systems only present metadata of papers as search results, which requires users to read the entire abstracts to understand the brief contents of the returned papers. |
| Approach: | They propose to use a knowledge graph extracted from abstracts of 23k papers on arXiv’s cs.CL category to augment search results with relevant details and explanations. |
| Outcome: | The proposed platform can accelerate the users’ search process with paper explanations and helps them better explore the landscape of the topics of interest. |
Trafilatura: A Web Scraping Library and Command-Line Tool for Text Discovery and Extraction (2021.acl-demo)
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| Challenge: | Existing tools for text extraction and web corpus construction are not enough to extract and pre-process web data to meet scientific expectations with respect to text quality. |
| Approach: | They propose a text discovery and extraction tool published under open-source license that allows for main text, comments and metadata extraction while also providing building blocks for web crawling tasks. |
| Outcome: | The proposed tool performs significantly better than other open-source solutions on real-world data and in external benchmarks. |
Dodrio: Exploring Transformer Models with Interactive Visualization (2021.acl-demo)
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| Challenge: | Recent research suggests the key may lie in multi-headed attention mechanism’s ability to learn and represent linguistic information. |
| Approach: | They present an open-source visualization tool to analyze attention mechanisms in transformer-based models with linguistic knowledge. |
| Outcome: | Dodrio analyzes attention mechanisms in transformer-based models with linguistic knowledge. |
REM: Efficient Semi-Automated Real-Time Moderation of Online Forums (2021.acl-demo)
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| Challenge: | REM is a tool for the semi-automated real-time moderation of large scale online forums. |
| Approach: | They propose a semi-automated real-time moderation tool for large scale online forums that maximizes the efficiency of manual moderation by targeting only those comments for which human intervention is needed. |
| Outcome: | The proposed method maximizes the efficiency of manual moderation by targeting only those comments for which human intervention is needed, e.g. due to high classification uncertainty. |
SummVis: Interactive Visual Analysis of Models, Data, and Evaluation for Text Summarization (2021.acl-demo)
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| Challenge: | despite advances in abstractive text summarization, the true performance and failure modes of modern neural models are not yet fully understood due to the black-box nature of neural models and unmanageable scale of recent datasets for manual analysis. |
| Approach: | They propose an open-source tool for visualizing abstractive summaries that enables fine-grained analysis of models, data, and evaluation metrics associated with text summarization. |
| Outcome: | The proposed tool can identify the shortcomings and failure modes of state-of-the-art summarization models. |
A Graphical Interface for Curating Schemas (2021.acl-demo)
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| Challenge: | Existing work on analyzing information extracted from documents has focused on examining the model understanding of complex schemas. |
| Approach: | They propose a curation interface that takes an IE system’s output in a pre-defined format and generates a graphical representation of its elements. |
| Outcome: | The proposed interface can be used to edit and prune schemas for complex events like Improvised Explosive Device (IED) based scenarios. |
TEXTOIR: An Integrated and Visualized Platform for Text Open Intent Recognition (2021.acl-demo)
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| Challenge: | TEXTOIR is the first integrated platform for text open intent recognition . currently, many dialogue systems are limited to handle the uncertain open intents . |
| Approach: | TEXTOIR is the first integrated platform for text open intent recognition . it is composed of two main modules: open intent detection and open intent discovery . authors propose a framework to implement a complete process to identify known intents and discover open intents . |
| Outcome: | TEXTOIR is the first integrated and visualized platform for text open intent recognition . it integrates state-of-the-art algorithms and benchmark intent datasets . however, there are still some issues, which bring difficulties for future research . |
KuiLeiXi: a Chinese Open-Ended Text Adventure Game (2021.acl-demo)
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Yadong Xi, Xiaoxi Mao, Le Li, Lei Lin, Yanjiang Chen, Shuhan Yang, Xuhan Chen, Kailun Tao, Zhi Li, Gongzheng Li, Lin Jiang, Siyan Liu, Zeng Zhao, Minlie Huang, Changjie Fan, Zhipeng Hu
| Challenge: | Recent advances in pre-trained language models have made it possible to generate human-like text. |
| Approach: | They propose to integrate an open-ended text adventure game in Chinese, named KuiLeiXi, where players interact with the AI until the plot goals are reached. |
| Outcome: | The proposed game lacks incentives and relies on players to explore on their own. |
CRSLab: An Open-Source Toolkit for Building Conversational Recommender System (2021.acl-demo)
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Kun Zhou, Xiaolei Wang, Yuanhang Zhou, Chenzhan Shang, Yuan Cheng, Wayne Xin Zhao, Yaliang Li, Ji-Rong Wen
| Challenge: | Existing studies on conversational recommender systems lack a unified and standardized implementation or comparison. |
| Approach: | They propose to use a unified framework and highly-decoupled modules to develop CRSs. |
| Outcome: | The proposed framework collects 6 commonly used human-annotated CRS datasets and implements 19 models that include advanced techniques such as graph neural networks and pre-training models. |
Does My Representation Capture X? Probe-Ably (2021.acl-demo)
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| Challenge: | Probing (or diagnostic classification) has become a popular strategy for investigating whether a given set of intermediate features is present in the representations of neural models. |
| Approach: | They propose to use an extendable probing framework to automate the application of probing methods to the user’s inputs. |
| Outcome: | The proposed framework automates the application of probing methods to the user’s inputs. |
CLTR: An End-to-End, Transformer-Based System for Cell-Level Table Retrieval and Table Question Answering (2021.acl-demo)
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| Challenge: | Existing systems that retrieve tables based on keyword queries and table contents often result in poor quality . a growing demand for natural language questions over tables to be used for QA . |
| Approach: | They propose an end-to-end transformer-based table question answering system that takes natural language questions and massive table corpora as inputs to retrieve the most relevant tables. |
| Outcome: | The proposed system can retrieve relevant tables and locate the correct cells to answer questions. |
Neural Extractive Search (2021.acl-demo)
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| Challenge: | a domain expert often needs to extract structured information from large corpora. |
| Approach: | They propose a search paradigm called "extractive search" that extends search queries with capture-slots to allow for rapid extraction. |
| Outcome: | The proposed search paradigm can be extended with neural similarity techniques. |
FastSeq: Make Sequence Generation Faster (2021.acl-demo)
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Yu Yan, Fei Hu, Jiusheng Chen, Nikhil Bhendawade, Ting Ye, Yeyun Gong, Nan Duan, Desheng Cui, Bingyu Chi, Ruofei Zhang
| Challenge: | Transformer-based models have made tremendous impact in natural language generation, but inference speed is still a bottleneck due to large model size and intensive computing involved in auto-regressive decoding process. |
| Approach: | They propose an attention cache optimization, an efficient algorithm for detecting repeated n-grams, and an asynchronous generation pipeline with parallel I/O to accelerate sequence generation without loss of accuracy. |
| Outcome: | The proposed framework can accelerate the sequence generation by 4x to 9x with a simple one-line code change for a set of widely used and diverse models. |
LOA: Logical Optimal Actions for Text-based Interaction Games (2021.acl-demo)
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Daiki Kimura, Subhajit Chaudhury, Masaki Ono, Michiaki Tatsubori, Don Joven Agravante, Asim Munawar, Akifumi Wachi, Ryosuke Kohita, Alexander Gray
| Challenge: | et al., 2019) have proposed a neuro-symbolic approach for reinforcement learning in non-simultaneous environments. |
| Approach: | They propose an action decision architecture with a neuro-symbolic framework for natural language interaction games. |
| Outcome: | The proposed framework provides an open-source implementation in Python for the reinforcement learning environment to facilitate an experiment for studying neuro-symbolic agents. |
ProphetNet-X: Large-Scale Pre-training Models for English, Chinese, Multi-lingual, Dialog, and Code Generation (2021.acl-demo)
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Weizhen Qi, Yeyun Gong, Yu Yan, Can Xu, Bolun Yao, Bartuer Zhou, Biao Cheng, Daxin Jiang, Jiusheng Chen, Ruofei Zhang, Houqiang Li, Nan Duan
| Challenge: | Existing models for pre-training are not convenient for users to find and set them up. |
| Approach: | They propose to extend ProphetNet into other domains and languages by pre-training models . they pre-train a cross-lingual generation model ProphetNet-Multi and a Chinese generation model . |
| Outcome: | The proposed models achieve new state-of-the-art on 10 benchmarks. |
IFlyEA: A Chinese Essay Assessment System with Automated Rating, Review Generation, and Recommendation (2021.acl-demo)
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| Challenge: | Automated Essay Assessment (AEA) aims to judge students’ writing proficiency in an automatic way. |
| Approach: | They propose to use Chinese AEA system IFlyEssayAssess to evaluate essays written by native Chinese students from primary and junior schools. |
| Outcome: | The proposed system provides application services for essay scoring, review generation, recommendation, and explainable analytical visualization. |
Ecco: An Open Source Library for the Explainability of Transformer Language Models (2021.acl-demo)
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| Challenge: | Existing models that use the Transformer architecture are lag behind our ability to scale them. |
| Approach: | They propose an open-source library for the explainability of Transformer-based NLP models that captures, analyzes, visualizes, and interactively explores the inner mechanics of these models. |
| Outcome: | The proposed tools capture, analyze, visualize, and explore the inner workings of Transformer-based language models. |
PAWLS: PDF Annotation With Labels and Structure (2021.acl-demo)
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| Challenge: | Existing tools for annotation of PDFs are limited to a web browser, allowing users to extract semantically meaningful regions from PDFs. |
| Approach: | They propose an annotation tool specifically designed for Adobe’s Portable Document Format (PDF) PAWLS supports span-based textual annotation, N-ary relations and freeform, non-textual bounding boxes. |
| Outcome: | The proposed tool supports span-based textual annotation, N-ary relations and freeform, non-textual bounding boxes. |
TweeNLP: A Twitter Exploration Portal for Natural Language Processing (2021.acl-demo)
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| Challenge: | Currently, Twitter curates 19,395 tweets from various NLP conferences and general NLP discussions. |
| Approach: | They propose to integrate tweets pertaining to research papers with the NLPExplorer scientific literature search engine to organize Twitter's natural language processing data. |
| Outcome: | The proposed system curates 19,395 tweets from various NLP conferences and general discussions. |
ChrEnTranslate: Cherokee-English Machine Translation Demo with Quality Estimation and Corrective Feedback (2021.acl-demo)
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| Challenge: | a new study shows that machine translation models can translate fragments of the source sentence but make major mistakes. |
| Approach: | They propose an online machine translation demonstration system for translation between English and an endangered language Cherokee. |
| Outcome: | The proposed system achieves state-of-the-art translation performance and improves quality estimation . the proposed system can translate between English and an endangered language Cherokee . |
ExplainaBoard: An Explainable Leaderboard for NLP (2021.acl-demo)
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Pengfei Liu, Jinlan Fu, Yang Xiao, Weizhe Yuan, Shuaichen Chang, Junqi Dai, Yixin Liu, Zihuiwen Ye, Graham Neubig
| Challenge: | Using leaderboards, researchers can track the performance of various systems on various NLP tasks. |
| Approach: | They propose a new conceptualization and implementation of NLP evaluation using a leaderboard. |
| Outcome: | The ExplainaBoard is an evaluation tool for natural language processing (NLP) it covers more than 400 systems, 50 datasets, 40 languages, and 12 tasks. |
Exploring Word Usage Change with Continuously Evolving Embeddings (2021.acl-demo)
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| Challenge: | a new method to track word usage changes is proposed for text datasets that are collected over a longer period of time. |
| Approach: | They propose a way to track word usage changes via continuously evolving embeddings . they demonstrate an interactive web app that can explore semantic shifts with interactive plots a text . |
| Outcome: | The proposed method can be used to analyze word usage changes with interactive plots. |
TURING: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interface (2021.acl-demo)
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Peng Xu, Wenjie Zi, Hamidreza Shahidi, Ákos Kádár, Keyi Tang, Wei Yang, Jawad Ateeq, Harsh Barot, Meidan Alon, Yanshuai Cao
| Challenge: | Existing text-to-SQL semantic parsers cannot achieve high accuracy in cross-database setting . TURING is a NLDB system that can be used to democratize data-driven insights for non-technical users . |
| Approach: | They propose a TURING system that provides high-precision natural language explanations of SQL queries in a beam. |
| Outcome: | The proposed system achieves 75.1% execution accuracy and 78.3% top-5 beam execution accuracy on the Spider validation set. |
Many-to-English Machine Translation Tools, Data, and Pretrained Models (2021.acl-demo)
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| Challenge: | Commercial translation systems support only one hundred languages or fewer . commercial translation systems do not make these models available for transfer to low resource languages . |
| Approach: | They propose a multilingual neural machine translation model that can translate from 500 source languages to English. |
| Outcome: | The proposed model can translate from 500 source languages to English, or be used as a parent model for low-resource languages. |
LEGOEval: An Open-Source Toolkit for Dialogue System Evaluation via Crowdsourcing (2021.acl-demo)
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| Challenge: | Currently, researchers use automatic metrics and human evaluation to evaluate dialogue systems. |
| Approach: | They propose to use a Python API to easily evaluate dialogue systems using Amazon Mechanical Turk. |
| Outcome: | The open-source toolkit provides a fast, consistent method for reproducing human evaluation results. |
ReTraCk: A Flexible and Efficient Framework for Knowledge Base Question Answering (2021.acl-demo)
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| Challenge: | Existing neural semantic parsing methods for knowledge base question answering are lacking . a generic and extensible framework is lacking for KBQA. |
| Approach: | They propose a neural semantic parsing framework for large scale knowledge base question answering . they propose 'retriever-transducer-checker' framework that provides a retriever and a transducer . |
| Outcome: | The proposed framework is ranked at top1 overall performance on the GrailQA leaderboard and achieves competitive performance on typical WebQuestionsSP benchmark. |
skweak: Weak Supervision Made Easy for NLP (2021.acl-demo)
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| Challenge: | skweak is a Python-based toolkit for NLP developers to use weak supervision . labelled data remains a scarce resource in many practical NLP scenarios . |
| Approach: | They present a Python-based toolkit that allows NLP developers to use weak supervision . skweak is designed to facilitate the use of weak supervision for NLP tasks . |
| Outcome: | skweak is a Python-based toolkit that facilitates weak supervision . the toolkit provides a simple interface to apply labels to a large corpus of text data . |
TextFlint: Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing (2021.acl-demo)
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Xiao Wang, Qin Liu, Tao Gui, Qi Zhang, Yicheng Zou, Xin Zhou, Jiacheng Ye, Yongxin Zhang, Rui Zheng, Zexiong Pang, Qinzhuo Wu, Zhengyan Li, Chong Zhang, Ruotian Ma, Zichu Fei, Ruijian Cai, Jun Zhao, Xingwu Hu, Zhiheng Yan, Yiding Tan, Yuan Hu, Qiyuan Bian, Zhihua Liu, Shan Qin, Bolin Zhu, Xiaoyu Xing, Jinlan Fu, Yue Zhang, Minlong Peng, Xiaoqing Zheng, Yaqian Zhou, Zhongyu Wei, Xipeng Qiu, Xuanjing Huang
| Challenge: | Existing approaches to textual robustness evaluation focus on slightly modifying the input data, which maintains the original meaning and results in a different prediction. |
| Approach: | They propose a multilingual robustness evaluation toolkit for NLP that integrates universal text transformations, task-specific transformations and adversarial attack. |
| Outcome: | The toolkit includes universal text transformation, task-specific transformation, adversarial attack, subpopulation, and their combinations to provide comprehensive robustness analyses. |
Stretch-VST: Getting Flexible With Visual Stories (2021.acl-demo)
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| Challenge: | Existing visual storytelling models produce stories with fixed lengths of five sentences and the fix-length stories carry limited details and provide ambiguous textual information to the readers. |
| Approach: | They propose to “stretch” visual storytelling frameworks by adding appropriate knowledge to the model to generate long stories. |
| Outcome: | The proposed framework provides better focus and detail when long stories are generated without deteriorating the quality. |
OpenAttack: An Open-source Textual Adversarial Attack Toolkit (2021.acl-demo)
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Guoyang Zeng, Fanchao Qi, Qianrui Zhou, Tingji Zhang, Zixian Ma, Bairu Hou, Yuan Zang, Zhiyuan Liu, Maosong Sun
| Challenge: | Various attack models are distinct and implemented with different programming frameworks and settings, which hinders quick utilization and fair comparison of attack models. |
| Approach: | They propose an open-source textual adversarial attack toolkit to solve these issues by combining 15 typical attack models into one toolkit. |
| Outcome: | The proposed toolkit supports all attack types, multilinguality, and parallel processing. |