Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
Xiaomingbot: A Multilingual Robot News Reporter (2020.acl-demos)
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Runxin Xu, Jun Cao, Mingxuan Wang, Jiaze Chen, Hao Zhou, Ying Zeng, Yuping Wang, Li Chen, Xiang Yin, Xijin Zhang, Songcheng Jiang, Yuxuan Wang, Lei Li
| Challenge: | Xiaomingbot is a multilingual and multimodal software robot with four capabilities: news generation, news translation, news reading and avatar animation. |
| Approach: | They propose to build a multilingual and multimodal software robot with four inte- gal capabilities: news generation, news translation, news reading and avatar animation. |
| Outcome: | The proposed system generates Chinese news, then reads it in multiple languages and generates an animated avatar reading it. |
TextBrewer: An Open-Source Knowledge Distillation Toolkit for Natural Language Processing (2020.acl-demos)
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| Challenge: | Large pre-trained language models have hundreds of millions of parameters and take several gigabytes of memory to train and inference. |
| Approach: | They propose an open-source knowledge distillation toolkit designed for natural language processing that provides a set of predefined distillation methods and can be extended with custom code. |
| Outcome: | The proposed method is comparable with or even higher than the public distilled BERT models with similar numbers of parameters. |
Syntactic Search by Example (2020.acl-demos)
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| Challenge: | a new system allows a user to search a large linguistically annotated corpus using syntactic patterns over dependency graphs. |
| Approach: | They propose a query language that allows a user to search a large linguistically annotated corpus using syntactic patterns over dependency graphs. |
| Outcome: | The proposed system searches the English wikipedia and English pubmed abstracts at a rapid speed. |
Tabouid: a Wikipedia-based word guessing game (2020.acl-demos)
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| Challenge: | Using Wikipedia articles, we generate word-guessing games using a set of NLP and machine-learning techniques. |
| Approach: | They propose a system which uses Wikipedia to generate word-guessing games. |
| Outcome: | The proposed game is based on Tabouid, a word-guessing board game originally published by Parker Brothers in 1989. |
Talk to Papers: Bringing Neural Question Answering to Academic Search (2020.acl-demos)
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| Challenge: | Talk to Papers aims to improve the current experience of academic search by using open-domain question answering (QA) techniques. |
| Approach: | They propose to use open-domain question answering techniques to improve the current experience of academic search by combining natural language queries with machine reading at scale. |
| Outcome: | The proposed tool improves on existing search engines and provides a collaborative data collection tool to curate the first natural language processing research QA dataset. |
Personalized PageRank with Syntagmatic Information for Multilingual Word Sense Disambiguation (2020.acl-demos)
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| Challenge: | SyntagRank is a knowledge-based WSD system that exploits syntagmatic information to perform state-of-the-art knowledge-driven WSD in a multilingual setting. |
| Approach: | They propose to exploit syntagmatic information to perform state-of-the-art knowledge-based WSD in a multilingual setting by using a Web interface and a RESTful API. |
| Outcome: | SyntagRank exploits disambiguated pairs of words in SyntagNet to perform state-of-the-art knowledge-based WSD in a multilingual setting. |
pyBART: Evidence-based Syntactic Transformations for IE (2020.acl-demos)
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| Challenge: | Syntactic dependencies are designed to accurately reflect syntactical relations, but they do not make semantic relations explicit. |
| Approach: | They propose a Python library for converting English Enhanced UD trees to Enhanced or Enhanced representations. |
| Outcome: | The proposed representations are linguistically sound and make lexical relations explicit . the proposed representation scores higher than Enhanced UD graphs, while requiring fewer patterns. |
EVIDENCEMINER: Textual Evidence Discovery for Life Sciences (2020.acl-demos)
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Xuan Wang, Yingjun Guan, Weili Liu, Aabhas Chauhan, Enyi Jiang, Qi Li, David Liem, Dibakar Sigdel, John Caufield, Peipei Ping, Jiawei Han
| Challenge: | EVIDENCEMINER is a web-based system that allows users to query a natural language statement and retrieve textual evidence from a background corpora for life sciences. |
| Approach: | They propose a web-based system that lets users query a natural language statement and automatically retrieves textual evidence from a background corpora for life sciences. |
| Outcome: | EVIDENCEMINER is a web-based system that lets users query a natural language statement and automatically retrieves textual evidence from a background corpora for life sciences. |
Trialstreamer: Mapping and Browsing Medical Evidence in Real-Time (2020.acl-demos)
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| Challenge: | Trialstreamer extracts key pieces of information that clinicians need when appraising the literature . the highest-quality evidence to inform healthcare practice comes from randomized controlled trials . |
| Approach: | They propose a system that extracts key pieces of information from biomedical abstracts and combines them into a database of clinical trial reports. |
| Outcome: | The proposed system extracts descriptions of trial participants, treatments compared in each arm, and which outcomes were measured. |
SyntaxGym: An Online Platform for Targeted Evaluation of Language Models (2020.acl-demos)
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| Challenge: | SyntaxGym is an online platform and open-source framework for targeted syntactic evaluation of neural network language models. |
| Approach: | They propose to make targeted syntactic evaluations accessible to both experts in NLP and linguistics and reproducible across computing environments. |
| Outcome: | The proposed framework is reproducible across computing environments and standardized following the norms of psycholinguistic experimental design. |
GAIA: A Fine-grained Multimedia Knowledge Extraction System (2020.acl-demos)
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Manling Li, Alireza Zareian, Ying Lin, Xiaoman Pan, Spencer Whitehead, Brian Chen, Bo Wu, Heng Ji, Shih-Fu Chang, Clare Voss, Daniel Napierski, Marjorie Freedman
| Challenge: | Open source knowledge extraction tools are used for many real-world applications, but there is no comprehensive system for KE. |
| Approach: | They propose a multimedia knowledge extraction system that takes multimedia data from various sources and languages as input and creates a coherent, structured knowledge base. |
| Outcome: | The system achieves top performance at the recent NIST TAC SM-KBP2019 evaluation. |
Multilingual Universal Sentence Encoder for Semantic Retrieval (2020.acl-demos)
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Yinfei Yang, Daniel Cer, Amin Ahmad, Mandy Guo, Jax Law, Noah Constant, Gustavo Hernandez Abrego, Steve Yuan, Chris Tar, Yun-hsuan Sung, Brian Strope, Ray Kurzweil
| Challenge: | Using a multi-task trained dual-encoder, our models embed text from 16 languages into a shared semantic space. |
| Approach: | They propose retrieval focused multilingual sentence embedding models on TensorFlow Hub. |
| Outcome: | The models achieve state-of-the-art on monolingual and cross-lingual retrieval (SR) and retrieval question answering (ReQA) competitive performance is obtained on related tasks of translation pair bitext retrieval and retrieving question answering. |
BENTO: A Visual Platform for Building Clinical NLP Pipelines Based on CodaLab (2020.acl-demos)
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| Challenge: | CodaLab has limited support for creating reusable tools that can be easily applied to different datasets and composed into pipelines. |
| Approach: | They propose a workflow management platform with a graphic user interface built on top of CodaLab to facilitate the process of building clinical NLP pipelines. |
| Outcome: | The proposed workflow management platform, BENTO, is designed for clinical NLP tasks and can be easily used by researchers and developers. |
Stanza: A Python Natural Language Processing Toolkit for Many Human Languages (2020.acl-demos)
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| Challenge: | Existing tools that support only a few major languages are under-optimized for accuracy due to a focus on efficiency or use of less powerful models. |
| Approach: | They introduce a Python natural language processing toolkit that supports 66 languages . they train Stanza on 112 datasets and show it generalizes well on all languages compared to other tools . |
| Outcome: | The proposed toolkit performs well on 112 datasets and is compatible with the popular Java CoreNLP software. |
jiant: A Software Toolkit for Research on General-Purpose Text Understanding Models (2020.acl-demos)
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Yada Pruksachatkun, Phil Yeres, Haokun Liu, Jason Phang, Phu Mon Htut, Alex Wang, Ian Tenney, Samuel R. Bowman
| Challenge: | jiant is an open source toolkit for conducting multitask and transfer learning experiments on English NLU tasks. |
| Approach: | They introduce jiant, an open source toolkit for conducting multitask and transfer learning experiments on English NLU tasks. |
| Outcome: | The proposed toolkit reproduces published performance on GLUE and SuperGLUE tasks. |
The Microsoft Toolkit of Multi-Task Deep Neural Networks for Natural Language Understanding (2020.acl-demos)
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Xiaodong Liu, Yu Wang, Jianshu Ji, Hao Cheng, Xueyun Zhu, Emmanuel Awa, Pengcheng He, Weizhu Chen, Hoifung Poon, Guihong Cao, Jianfeng Gao
| Challenge: | MT-DNN is an open-source natural language understanding toolkit . it allows researchers and developers to train customized deep learning models . |
| Approach: | They present MT-DNN, an open-source natural language understanding toolkit . it is designed to facilitate rapid customization for a broad spectrum of NLU tasks . MT supports multi-task knowledge distillation, which can substantially compress a deep neural model without significant performance drop. |
| Outcome: | The proposed model can significantly compress a large model without significant performance drop. |
LinggleWrite: a Coaching System for Essay Writing (2020.acl-demos)
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| Challenge: | Existing writing services that provide feedback on writing skills are not providing sufficient "coaching" information. |
| Approach: | They propose a writing coach that provides writing suggestions, assesses writing proficiency levels, detects grammatical errors, and offers corrective feedback in response to user’s essay. |
| Outcome: | The proposed system improves on public test sets and shows that both AES and GED models achieve state-of-the-art performance. |
CLIReval: Evaluating Machine Translation as a Cross-Lingual Information Retrieval Task (2020.acl-demos)
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| Challenge: | evaluating machine translation (MT) with cross-lingual information retrieval is relatively time-consuming and subjective. |
| Approach: | They propose a toolkit that evaluates machine translation with a proxy task of cross-lingual information retrieval. |
| Outcome: | The proposed toolkit is based on the "metrics shared task" of WMT2019. |
ConvLab-2: An Open-Source Toolkit for Building, Evaluating, and Diagnosing Dialogue Systems (2020.acl-demos)
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Qi Zhu, Zheng Zhang, Yan Fang, Xiang Li, Ryuichi Takanobu, Jinchao Li, Baolin Peng, Jianfeng Gao, Xiaoyan Zhu, Minlie Huang
| Challenge: | ConvLab-2 inherits Convlab's framework but integrates more powerful dialogue models and supports more datasets. |
| Approach: | They present ConvLab-2, an open-source toolkit that enables researchers to build task-oriented dialogue systems with state-of-the-art models and perform an end-to-end evaluation. |
| Outcome: | The new tool inherits ConvLab's framework and extends it by integrating many recently proposed state-of-the-art dialogue models. |
OpusFilter: A Configurable Parallel Corpus Filtering Toolbox (2020.acl-demos)
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| Challenge: | OpusFilter is a toolbox for filtering parallel corpora using noisy training data. |
| Approach: | They propose a toolbox for filtering parallel corpora with heuristic filters, language identification libraries, character-based language models and word alignment tools. |
| Outcome: | The proposed tool outperforms a similar tool on a Finnish-English news translation task using noisy web crawls. |
Label Noise in Context (2020.acl-demos)
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| Challenge: | Label noise—incorrectly or ambiguously labeled training examples—can negatively impact model performance. |
| Approach: | They propose a noise-detection method that uses an example's neighborhood within the training set to reduce false positives and provide an explanation as to why the ex ample was flagged as noise. |
| Outcome: | The proposed method outperforms the state-of-the-art on precision and F0.5-score on short-text classification datasets. |
exBERT: A Visual Analysis Tool to Explore Learned Representations in Transformer Models (2020.acl-demos)
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| Challenge: | Large Transformer-based language models can route and reshape complex information via their multi-headed attention mechanism. |
| Approach: | They propose a tool to help humans conduct flexible, interactive investigations and formulate hypotheses for the model-internal reasoning process. |
| Outcome: | Using exBERT, we can analyze the representations and attentions of large language models and extend them to previously not analyzed models. |
Nakdan: Professional Hebrew Diacritizer (2020.acl-demos)
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| Challenge: | a system for automatic diacritization of Hebrew Text is available for both casual and expert users. |
| Approach: | They propose a system for automatic diacritization of Hebrew Text . the system combines declarative linguistic knowledge with machine learning models . |
| Outcome: | The proposed system is available for both casual and expert users. |
Photon: A Robust Cross-Domain Text-to-SQL System (2020.acl-demos)
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Jichuan Zeng, Xi Victoria Lin, Steven C.H. Hoi, Richard Socher, Caiming Xiong, Michael Lyu, Irwin King
| Challenge: | Existing natural language interfaces to databases are ambiguous or untranslatable . we present a robust, modular cross-domain text-to-SQL system . |
| Approach: | They propose a system that flags natural language input to which a SQL mapping cannot be immediately determined. |
| Outcome: | The proposed system can flag natural language input to which a SQL mapping cannot be determined. |
Interactive Task Learning from GUI-Grounded Natural Language Instructions and Demonstrations (2020.acl-demos)
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| Challenge: | SUGILITE is an intelligent task automation agent that can learn new tasks and relevant associated concepts interactively from the user’s natural language instructions and demonstrations using GUIs. |
| Approach: | They propose to use third-party mobile apps to teach new tasks and concepts using verbal instructions and demonstrations. |
| Outcome: | The proposed system can learn new tasks and relevant concepts from user's natural language instructions and demonstrations, and it generalizes taught concepts to different contexts and task domains. |
MixingBoard: a Knowledgeable Stylized Integrated Text Generation Platform (2020.acl-demos)
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| Challenge: | Neural text generation algorithms have seen great improvements over the past several years. |
| Approach: | They propose a platform for quickly building demos with a focus on knowledge grounded stylized text generation. |
| Outcome: | The proposed framework unifies existing text generation algorithms in a shared codebase and further adapts earlier algorithms for constrained generation. |
NLP Scholar: An Interactive Visual Explorer for Natural Language Processing Literature (2020.acl-demos)
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| Challenge: | aCL Anthology and Google Scholar provide a single dataset of NLP papers and their meta-information . authors describe interactive visualizations that present various aspects of the data . |
| Approach: | They propose to use citation data from the ACL Anthology and Google Scholar to create a unified dataset of NLP papers and their meta-information. |
| Outcome: | The proposed dataset includes papers published in the area of their interest and by specified authors. |
Stimulating Creativity with FunLines: A Case Study of Humor Generation in Headlines (2020.acl-demos)
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| Challenge: | FunLines is an online game that allows players to generate and rate funny news headlines . it is difficult to generate data that depends on human creativity, and measuring creativity often requires more effort. |
| Approach: | They propose a game where players edit news headlines to make them funny and rate the funniness of headlines edited by others. |
| Outcome: | The proposed game outperforms other crowdsourcing approaches in generating humor datasets. |
Usnea: An Authorship Tool for Interactive Fiction using Retrieval Based Semantic Parsing (2020.acl-demos)
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| Challenge: | Interactive Fiction is a genre of art and entertainment that is well known in the context of video games . authorship tools for IF define some structure of a story and provide suggested algorithms or software itself to realize this structure in a form that a reader can digest . |
| Approach: | They propose to use retrieval based semantic parsing to create a novel type of Interactive Fiction. |
| Outcome: | The proposed novel type of Interactive Fiction is open-source and features novel algorithms and models based on the IF community's existing models. |
DIALOGPT : Large-Scale Generative Pre-training for Conversational Response Generation (2020.acl-demos)
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Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, Bill Dolan
| Challenge: | DIALOGPT is a large, tunable neural conversational response generation model . trained on 147M conversation-like exchanges extracted from Reddit comment chains . |
| Approach: | They present a large, tunable neural conversational response generation model, DIALOGPT . the model is trained on 147M conversation-like exchanges extracted from Reddit comment chains . |
| Outcome: | The proposed model can generate more relevant, contentful and context-consistent responses than baseline systems. |
ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents (2020.acl-demos)
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Chia-Yu Li, Daniel Ortega, Dirk Väth, Florian Lux, Lindsey Vanderlyn, Maximilian Schmidt, Michael Neumann, Moritz Völkel, Pavel Denisov, Sabrina Jenne, Zorica Kacarevic, Ngoc Thang Vu
| Challenge: | Existing toolkits for developing dialog systems are limited to core components and do not support multi-modal processing and social signals. |
| Approach: | They propose to use ADVISER to develop multi-modal dialog agents using multi-text and social signals. |
| Outcome: | The proposed toolkit is flexible, easy to use, and easy to extend for linguists and cognitive scientists, thereby providing a flexible platform for collaborative research. |
Prta: A System to Support the Analysis of Propaganda Techniques in the News (2020.acl-demos)
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Giovanni Da San Martino, Shaden Shaar, Yifan Zhang, Seunghak Yu, Alberto Barrón-Cedeño, Preslav Nakov
| Challenge: | recent events have brought the public attention to the dangers of online disinformation. |
| Approach: | a new tool helps users analyze propaganda using specific rhetorical and psychological techniques. a prta system identifies the spans in which propaganda techniques occur and compares them. |
| Outcome: | a new tool can analyze articles crawled on a regular basis and compare them on the basis of their use of propaganda techniques. |
Clinical-Coder: Assigning Interpretable ICD-10 Codes to Chinese Clinical Notes (2020.acl-demos)
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| Challenge: | Existing methods of automatic coding prediction have been successful, but the interpretability of predicted codes is a challenge. |
| Approach: | They propose an online system that can predict ICD codes for Chinese clinical notes by using a Dilated Convolutional Attention network with N-gram Matching mechanism. |
| Outcome: | The proposed system is able to provide supporting information in clinical decision making. |
ESPnet-ST: All-in-One Speech Translation Toolkit (2020.acl-demos)
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Hirofumi Inaguma, Shun Kiyono, Kevin Duh, Shigeki Karita, Nelson Yalta, Tomoki Hayashi, Shinji Watanabe
| Challenge: | ESPnet-ST is a new project for the quick development of speech-to-speech translation systems. |
| Approach: | They propose a framework for rapid development of speech-to-speech translation systems . they provide all-in-one recipes including data pre-processing, feature extraction, training, and decoding pipelines . |
| Outcome: | The proposed model outperforms the current state-of-the-art models on a wide range of benchmark datasets. |
Penman: An Open-Source Library and Tool for AMR Graphs (2020.acl-demos)
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| Challenge: | Abstract Meaning Representation encodes acyclic graphs in PENMAN notation format . the open-source Python library Penman provides a robust parser and functions for graph inspection and manipulation . |
| Approach: | They propose a framework for encoding acyclic graphs in PENMAN notation . the open-source Python library Penman provides a robust parser and functions for graph inspection and manipulation . |
| Outcome: | The open-source Python library Penman provides a robust parser, functions for graph inspection and manipulation, and functions for formatting graphs into PENMAN notation. |
Embedding-based Scientific Literature Discovery in a Text Editor Application (2020.acl-demos)
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| Challenge: | Despite the availability of powerful search engines and text editing software, discovering relevant papers and integrating the knowledge into a manuscript remain complex tasks associated with high cognitive load. |
| Approach: | They propose to combine text editing and literature discovery in an interactive user interface with a search engine that couples Boolean keyword filtering with nearest neighbor search over text embeddings. |
| Outcome: | The proposed application combines text editing and literature discovery in an interactive user interface. |
MMPE: A Multi-Modal Interface using Handwriting, Touch Reordering, and Speech Commands for Post-Editing Machine Translation (2020.acl-demos)
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Nico Herbig, Santanu Pal, Tim Düwel, Kalliopi Meladaki, Mahsa Monshizadeh, Vladislav Hnatovskiy, Antonio Krüger, Josef van Genabith
| Challenge: | a shift from traditional translation to post-editing (PE) of machine-translated text can save time and reduce errors, but it also affects the design of translation interfaces. |
| Approach: | They propose a prototype that combines traditional input modes with pen, touch, and speech modalities for post-editing of machine-translated (MT) they propose to use these modalités to cross out or hand-write new text, drag and drop words for reordering, or use spoken commands to update the text in place. |
| Outcome: | The proposed interfaces can be used to cross out or hand-write new text, drag and drop words for reordering, or use spoken commands to update the text in place. |
Torch-Struct: Deep Structured Prediction Library (2020.acl-demos)
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| Challenge: | Structured prediction is a key area of machine learning and is difficult to utilize in deep learning frameworks. |
| Approach: | They propose a library for structured prediction that integrates with vectorized, auto-differentiation based frameworks. |
| Outcome: | The library exploits auto-differentiation to produce readable, fast, and testable code. |
Conversation Learner - A Machine Teaching Tool for Building Dialog Managers for Task-Oriented Dialog Systems (2020.acl-demos)
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Swadheen Shukla, Lars Liden, Shahin Shayandeh, Eslam Kamal, Jinchao Li, Matt Mazzola, Thomas Park, Baolin Peng, Jianfeng Gao
| Challenge: | a wide variety of tasks have created a need for flexible task-oriented dialog systems . dialog flows are intuitively interpretable but lack the flexibility needed to handle complex dialogs . |
| Approach: | They propose a machine teaching tool for building dialog managers using familiar tools . they convert the dialog flow into a parametric model and use user-system dialog logs as training data . |
| Outcome: | The proposed tool combines the best of both approaches to build dialog managers . it converts the dialog flow into a parametric model and improves it over time . |
NSTM: Real-Time Query-Driven News Overview Composition at Bloomberg (2020.acl-demos)
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Joshua Bambrick, Minjie Xu, Andy Almonte, Igor Malioutov, Guim Perarnau, Vittorio Selo, Iat Chong Chan
| Challenge: | aggregators consume millions of articles every day, making it difficult to quickly identify key events and miss less-reported stories. |
| Approach: | a new kind of summarization engine was needed to condense large volumes of news into short, easy to absorb points. |
| Outcome: | NSTM can be used to summarize news articles in seconds and quickly and efficiently. |
SUPP.AI: finding evidence for supplement-drug interactions (2020.acl-demos)
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Lucy Lu Wang, Oyvind Tafjord, Arman Cohan, Sarthak Jain, Sam Skjonsberg, Carissa Schoenick, Nick Botner, Waleed Ammar
| Challenge: | Dietary supplements are used by a large portion of the population, but information on their pharmacologic interactions is incomplete. |
| Approach: | They propose an application to search evidence sentences extracted from the literature to identify supplement-drug interactions. |
| Outcome: | The proposed model extracts supplement information and identifies interactions using labeled DDI data. |
LEAN-LIFE: A Label-Efficient Annotation Framework Towards Learning from Explanation (2020.acl-demos)
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Dong-Ho Lee, Rahul Khanna, Bill Yuchen Lin, Seyeon Lee, Qinyuan Ye, Elizabeth Boschee, Leonardo Neves, Xiang Ren
| Challenge: | Existing frameworks for sequence labeling and classification require massive human effort and labeling data is limited. |
| Approach: | They propose a web-based, Label-Efficient AnnotatioN framework that allows an annotator to provide the needed labels for a task and can capture explanations for each labeling decision. |
| Outcome: | The proposed framework surpasses baseline F1 scores by 5-10 percentage points while using 2X times fewer labeled instances. |
What’s The Latest? A Question-driven News Chatbot (2020.acl-demos)
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| Challenge: | a news chatbot that draws content from news articles creates conversations with a user about the news. |
| Approach: | They describe an automatic news chatbot that draws content from a diverse set of news sources and creates conversations with a user about the news. |
| Outcome: | The proposed system engages news readers in multi-turn conversations about specific stories. |