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Natural Language Rationales with Full-Stack Visual Reasoning: From Pixels to Semantic Frames to Commonsense Graphs
Ana Marasović, Chandra Bhagavatula, J. Park, Ronan Le Bras, Noah A. Smith, Yejin ChoiFindings of EMNLP • 2020 Natural language rationales could provide intuitive, higher-level explanations that are easily understandable by humans, complementing the more broadly studied lower-level explanations based on gradients or attention weights. We present the first study…OCNLI: Original Chinese Natural Language Inference
H. Hu, Kyle Richardson, Liang Xu, L. Li, Sandra Kübler, L. MossFindings of EMNLP • 2020 Despite the tremendous recent progress on natural language inference (NLI), driven largely by large-scale investment in new datasets (e.g., SNLI, MNLI) and advances in modeling, most progress has been limited to English due to a lack of reliable datasets for…Parsing with Multilingual BERT, a Small Treebank, and a Small Corpus
Ethan C. Chau, Lucy H. Lin, Noah A. SmithFindings of EMNLP • 2020 Pretrained multilingual contextual representations have shown great success, but due to the limits of their pretraining data, their benefits do not apply equally to all language varieties. This presents a challenge for language varieties unfamiliar to these…PlotMachines: Outline-Conditioned Generation with Dynamic Plot State Tracking
Hannah Rashkin, Asli Celikyilmaz, Yejin Choi, Jianfeng GaoEMNLP • 2020 We propose the task of outline-conditioned story generation: given an outline as a set of phrases that describe key characters and events to appear in a story, the task is to generate a coherent narrative that is consistent with the provided outline. This…Plug and Play Autoencoders for Conditional Text Generation
Florian Mai, Nikolaos Pappas, I. Montero, Noah A. SmithEMNLP • 2020 Text autoencoders are commonly used for conditional generation tasks such as style transfer. We propose methods which are plug and play, where any pretrained autoencoder can be used, and only require learning a mapping within the autoencoder's embedding space…PowerTransformer: Unsupervised Controllable Revision for Biased Language Correction
Xinyao Ma, Maarten Sap, Hannah Rashkin, Yejin ChoiEMNLP • 2020 Unconscious biases continue to be prevalent in modern text and media, calling for algorithms that can assist writers with bias correction. For example, a female character in a story is often portrayed as passive and powerless (“She daydreams about being a…QADiscourse - Discourse Relations as QA Pairs: Representation, Crowdsourcing and Baselines
Valentina Pyatkin, Ayal Klein, Reut Tsarfaty, Ido DaganEMNLP • 2020 Discourse relations describe how two propositions relate to one another, and identifying them automatically is an integral part of natural language understanding. However, annotating discourse relations typically requires expert annotators. Recently…RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, Noah A. SmithFindings of EMNLP • 2020 Pretrained neural language models (LMs) are prone to generating racist, sexist, or otherwise toxic language which hinders their safe deployment. We investigate the extent to which pretrained LMs can be prompted to generate toxic language, and the…SciSight: Combining faceted navigation and research group detection for COVID-19 exploratory scientific search
Tom Hope, Jason Portenoy, Kishore Vasan, Jonathan Borchardt, Eric Horvitz, Daniel S. Weld, Marti A. Hearst, Jevin D. WestEMNLP • Demo • 2020 The COVID-19 pandemic has sparked unprecedented mobilization of scientists, already generating thousands of new papers that join a litany of previous biomedical work in related areas. This deluge of information makes it hard for researchers to keep track of…SLEDGE-Z: A Zero-Shot Baseline for COVID-19 Literature Search
S. MacAvaney, Arman Cohan, N. GoharianEMNLP • 2020 With worldwide concerns surrounding the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there is a rapidly growing body of literature on the virus. Clinicians, researchers, and policy-makers need a way to effectively search these articles. In…