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2,002.09836 | Fill in the BLANC: Human-free quality estimation of document summaries | ['Oleg Vasilyev', 'Vedant Dharnidharka', 'John Bohannon'] | ['cs.CL'] | We present BLANC, a new approach to the automatic estimation of document
summary quality. Our goal is to measure the functional performance of a summary
with an objective, reproducible, and fully automated method. Our approach
achieves this by measuring the performance boost gained by a pre-trained
language model with ... | 2020-02-23T06:21:43Z | 10 pages, 9 figures, 3 tables. In: Proceedings of the First Workshop
on Evaluation and Comparison of NLP Systems (Eval4NLP, Nov. 2020) p.11-20,
ACL | Proceedings of the First Workshop on Evaluation and Comparison of
NLP Systems (Nov.2020) 11-20 | null | Fill in the BLANC: Human-free quality estimation of document summaries | ['Oleg V. Vasilyev', 'Vedant Dharnidharka', 'John Bohannon'] | 2,020 | EVAL4NLP | 119 | 32 | ['Computer Science'] |
2,002.10857 | Circle Loss: A Unified Perspective of Pair Similarity Optimization | ['Yifan Sun', 'Changmao Cheng', 'Yuhan Zhang', 'Chi Zhang', 'Liang Zheng', 'Zhongdao Wang', 'Yichen Wei'] | ['cs.CV'] | This paper provides a pair similarity optimization viewpoint on deep feature
learning, aiming to maximize the within-class similarity $s_p$ and minimize the
between-class similarity $s_n$. We find a majority of loss functions, including
the triplet loss and the softmax plus cross-entropy loss, embed $s_n$ and $s_p$
int... | 2020-02-25T13:56:40Z | null | null | null | null | null | null | null | null | null | null |
2,002.10957 | MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression
of Pre-Trained Transformers | ['Wenhui Wang', 'Furu Wei', 'Li Dong', 'Hangbo Bao', 'Nan Yang', 'Ming Zhou'] | ['cs.CL'] | Pre-trained language models (e.g., BERT (Devlin et al., 2018) and its
variants) have achieved remarkable success in varieties of NLP tasks. However,
these models usually consist of hundreds of millions of parameters which brings
challenges for fine-tuning and online serving in real-life applications due to
latency and ... | 2020-02-25T15:21:10Z | Code and models:
https://github.com/microsoft/unilm/tree/master/minilm | null | null | null | null | null | null | null | null | null |
2,002.12328 | Few-shot Natural Language Generation for Task-Oriented Dialog | ['Baolin Peng', 'Chenguang Zhu', 'Chunyuan Li', 'Xiujun Li', 'Jinchao Li', 'Michael Zeng', 'Jianfeng Gao'] | ['cs.CL'] | As a crucial component in task-oriented dialog systems, the Natural Language
Generation (NLG) module converts a dialog act represented in a semantic form
into a response in natural language. The success of traditional template-based
or statistical models typically relies on heavily annotated data, which is
infeasible f... | 2020-02-27T18:48:33Z | Project website: https://aka.ms/scgpt ; Code and data:
https://github.com/pengbaolin/SC-GPT | null | null | null | null | null | null | null | null | null |
2,003.00104 | AraBERT: Transformer-based Model for Arabic Language Understanding | ['Wissam Antoun', 'Fady Baly', 'Hazem Hajj'] | ['cs.CL'] | The Arabic language is a morphologically rich language with relatively few
resources and a less explored syntax compared to English. Given these
limitations, Arabic Natural Language Processing (NLP) tasks like Sentiment
Analysis (SA), Named Entity Recognition (NER), and Question Answering (QA),
have proven to be very c... | 2020-02-28T22:59:24Z | Proceedings of the Twelfth International Conference on Language
Resources and Evaluation (LREC 2020), Marseille, France (2020) | null | null | null | null | null | null | null | null | null |
2,003.00196 | First Order Motion Model for Image Animation | ['Aliaksandr Siarohin', 'Stéphane Lathuilière', 'Sergey Tulyakov', 'Elisa Ricci', 'Nicu Sebe'] | ['cs.CV', 'cs.AI'] | Image animation consists of generating a video sequence so that an object in
a source image is animated according to the motion of a driving video. Our
framework addresses this problem without using any annotation or prior
information about the specific object to animate. Once trained on a set of
videos depicting objec... | 2020-02-29T07:08:56Z | NeurIPS 2019 | null | null | null | null | null | null | null | null | null |
2,003.00653 | Adversarial Attacks and Defenses on Graphs: A Review, A Tool and
Empirical Studies | ['Wei Jin', 'Yaxin Li', 'Han Xu', 'Yiqi Wang', 'Shuiwang Ji', 'Charu Aggarwal', 'Jiliang Tang'] | ['cs.LG', 'cs.CR', 'stat.ML'] | Deep neural networks (DNNs) have achieved significant performance in various
tasks. However, recent studies have shown that DNNs can be easily fooled by
small perturbation on the input, called adversarial attacks. As the extensions
of DNNs to graphs, Graph Neural Networks (GNNs) have been demonstrated to
inherit this v... | 2020-03-02T04:32:38Z | Accepted by SIGKDD Explorations | null | null | null | null | null | null | null | null | null |
2,003.00744 | PhoBERT: Pre-trained language models for Vietnamese | ['Dat Quoc Nguyen', 'Anh Tuan Nguyen'] | ['cs.CL', 'cs.AI'] | We present PhoBERT with two versions, PhoBERT-base and PhoBERT-large, the
first public large-scale monolingual language models pre-trained for
Vietnamese. Experimental results show that PhoBERT consistently outperforms the
recent best pre-trained multilingual model XLM-R (Conneau et al., 2020) and
improves the state-of... | 2020-03-02T10:21:17Z | EMNLP 2020 (Findings) | null | null | null | null | null | null | null | null | null |
2,003.01309 | Controllable Time-Delay Transformer for Real-Time Punctuation Prediction
and Disfluency Detection | ['Qian Chen', 'Mengzhe Chen', 'Bo Li', 'Wen Wang'] | ['cs.CL', 'cs.SD', 'eess.AS'] | With the increased applications of automatic speech recognition (ASR) in
recent years, it is essential to automatically insert punctuation marks and
remove disfluencies in transcripts, to improve the readability of the
transcripts as well as the performance of subsequent applications, such as
machine translation, dialo... | 2020-03-03T03:17:29Z | 4 pages, 2 figures, accepted by ICASSP 2020 | null | null | Controllable Time-Delay Transformer for Real-Time Punctuation Prediction and Disfluency Detection | ['Qian Chen', 'Mengzhe Chen', 'Bo Li', 'Wen Wang'] | 2,020 | IEEE International Conference on Acoustics, Speech, and Signal Processing | 36 | 35 | ['Computer Science', 'Engineering'] |
2,003.01355 | CLUECorpus2020: A Large-scale Chinese Corpus for Pre-training Language
Model | ['Liang Xu', 'Xuanwei Zhang', 'Qianqian Dong'] | ['cs.CL'] | In this paper, we introduce the Chinese corpus from CLUE organization,
CLUECorpus2020, a large-scale corpus that can be used directly for
self-supervised learning such as pre-training of a language model, or language
generation. It has 100G raw corpus with 35 billion Chinese characters, which is
retrieved from Common C... | 2020-03-03T06:39:27Z | 8 pages, 9 tables | null | null | CLUECorpus2020: A Large-scale Chinese Corpus for Pre-training Language Model | ['Liang Xu', 'Xuanwei Zhang', 'Qianqian Dong'] | 2,020 | arXiv.org | 71 | 14 | ['Computer Science'] |
2,003.0195 | AlignTTS: Efficient Feed-Forward Text-to-Speech System without Explicit
Alignment | ['Zhen Zeng', 'Jianzong Wang', 'Ning Cheng', 'Tian Xia', 'Jing Xiao'] | ['eess.AS', 'cs.CL', 'cs.SD'] | Targeting at both high efficiency and performance, we propose AlignTTS to
predict the mel-spectrum in parallel. AlignTTS is based on a Feed-Forward
Transformer which generates mel-spectrum from a sequence of characters, and the
duration of each character is determined by a duration predictor.Instead of
adopting the att... | 2020-03-04T08:44:32Z | will be presented in ICASSP 2020 | null | null | Aligntts: Efficient Feed-Forward Text-to-Speech System Without Explicit Alignment | ['Zhen Zeng', 'Jianzong Wang', 'Ning Cheng', 'Tian Xia', 'Jing Xiao'] | 2,020 | IEEE International Conference on Acoustics, Speech, and Signal Processing | 56 | 21 | ['Computer Science', 'Engineering'] |
2,003.02838 | Accelerator-aware Neural Network Design using AutoML | ['Suyog Gupta', 'Berkin Akin'] | ['eess.SP', 'cs.LG', 'stat.ML'] | While neural network hardware accelerators provide a substantial amount of
raw compute throughput, the models deployed on them must be co-designed for the
underlying hardware architecture to obtain the optimal system performance. We
present a class of computer vision models designed using hardware-aware neural
architec... | 2020-03-05T21:34:22Z | Accepted paper at the On-device Intelligence Workshop at MLSys
Conference 2020 | null | null | null | null | null | null | null | null | null |
2,003.05002 | TyDi QA: A Benchmark for Information-Seeking Question Answering in
Typologically Diverse Languages | ['Jonathan H. Clark', 'Eunsol Choi', 'Michael Collins', 'Dan Garrette', 'Tom Kwiatkowski', 'Vitaly Nikolaev', 'Jennimaria Palomaki'] | ['cs.CL', 'cs.LG'] | Confidently making progress on multilingual modeling requires challenging,
trustworthy evaluations. We present TyDi QA---a question answering dataset
covering 11 typologically diverse languages with 204K question-answer pairs.
The languages of TyDi QA are diverse with regard to their typology---the set of
linguistic fe... | 2020-03-10T21:11:53Z | To appear in Transactions of the Association for Computational
Linguistics (TACL) 2020. Please use this as the citation | null | null | null | null | null | null | null | null | null |
2,003.06505 | AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data | ['Nick Erickson', 'Jonas Mueller', 'Alexander Shirkov', 'Hang Zhang', 'Pedro Larroy', 'Mu Li', 'Alexander Smola'] | ['stat.ML', 'cs.LG'] | We introduce AutoGluon-Tabular, an open-source AutoML framework that requires
only a single line of Python to train highly accurate machine learning models
on an unprocessed tabular dataset such as a CSV file. Unlike existing AutoML
frameworks that primarily focus on model/hyperparameter selection,
AutoGluon-Tabular su... | 2020-03-13T23:10:39Z | null | null | null | null | null | null | null | null | null | null |
2,003.06713 | Document Ranking with a Pretrained Sequence-to-Sequence Model | ['Rodrigo Nogueira', 'Zhiying Jiang', 'Jimmy Lin'] | ['cs.IR', 'cs.LG'] | This work proposes a novel adaptation of a pretrained sequence-to-sequence
model to the task of document ranking. Our approach is fundamentally different
from a commonly-adopted classification-based formulation of ranking, based on
encoder-only pretrained transformer architectures such as BERT. We show how a
sequence-t... | 2020-03-14T22:29:50Z | null | null | null | null | null | null | null | null | null | null |
2,003.06792 | Learning Enriched Features for Real Image Restoration and Enhancement | ['Syed Waqas Zamir', 'Aditya Arora', 'Salman Khan', 'Munawar Hayat', 'Fahad Shahbaz Khan', 'Ming-Hsuan Yang', 'Ling Shao'] | ['cs.CV'] | With the goal of recovering high-quality image content from its degraded
version, image restoration enjoys numerous applications, such as in
surveillance, computational photography, medical imaging, and remote sensing.
Recently, convolutional neural networks (CNNs) have achieved dramatic
improvements over conventional ... | 2020-03-15T11:04:30Z | Accepted for publication at ECCV 2020 | null | null | null | null | null | null | null | null | null |
2,003.10286 | PathVQA: 30000+ Questions for Medical Visual Question Answering | ['Xuehai He', 'Yichen Zhang', 'Luntian Mou', 'Eric Xing', 'Pengtao Xie'] | ['cs.CL', 'cs.AI'] | Is it possible to develop an "AI Pathologist" to pass the board-certified
examination of the American Board of Pathology? To achieve this goal, the first
step is to create a visual question answering (VQA) dataset where the AI agent
is presented with a pathology image together with a question and is asked to
give the c... | 2020-03-07T17:55:41Z | null | null | null | null | null | null | null | null | null | null |
2,003.10555 | ELECTRA: Pre-training Text Encoders as Discriminators Rather Than
Generators | ['Kevin Clark', 'Minh-Thang Luong', 'Quoc V. Le', 'Christopher D. Manning'] | ['cs.CL'] | Masked language modeling (MLM) pre-training methods such as BERT corrupt the
input by replacing some tokens with [MASK] and then train a model to
reconstruct the original tokens. While they produce good results when
transferred to downstream NLP tasks, they generally require large amounts of
compute to be effective. As... | 2020-03-23T21:17:42Z | ICLR 2020 | null | null | null | null | null | null | null | null | null |
2,003.10564 | Improving Yorùbá Diacritic Restoration | ['Iroro Orife', 'David I. Adelani', 'Timi Fasubaa', 'Victor Williamson', 'Wuraola Fisayo Oyewusi', 'Olamilekan Wahab', 'Kola Tubosun'] | ['cs.CL'] | Yor\`ub\'a is a widely spoken West African language with a writing system
rich in orthographic and tonal diacritics. They provide morphological
information, are crucial for lexical disambiguation, pronunciation and are
vital for any computational Speech or Natural Language Processing tasks.
However diacritic marks are ... | 2020-03-23T22:07:15Z | Accepted to ICLR 2020 AfricaNLP workshop | null | null | null | null | null | null | null | null | null |
2,003.1108 | XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating
Cross-lingual Generalization | ['Junjie Hu', 'Sebastian Ruder', 'Aditya Siddhant', 'Graham Neubig', 'Orhan Firat', 'Melvin Johnson'] | ['cs.CL', 'cs.LG'] | Much recent progress in applications of machine learning models to NLP has
been driven by benchmarks that evaluate models across a wide variety of tasks.
However, these broad-coverage benchmarks have been mostly limited to English,
and despite an increasing interest in multilingual models, a benchmark that
enables the ... | 2020-03-24T19:09:37Z | In Proceedings of the 37th International Conference on Machine
Learning (ICML). July 2020 | null | null | null | null | null | null | null | null | null |
2,003.11982 | In defence of metric learning for speaker recognition | ['Joon Son Chung', 'Jaesung Huh', 'Seongkyu Mun', 'Minjae Lee', 'Hee Soo Heo', 'Soyeon Choe', 'Chiheon Ham', 'Sunghwan Jung', 'Bong-Jin Lee', 'Icksang Han'] | ['eess.AS', 'cs.SD'] | The objective of this paper is 'open-set' speaker recognition of unseen
speakers, where ideal embeddings should be able to condense information into a
compact utterance-level representation that has small intra-speaker and large
inter-speaker distance.
A popular belief in speaker recognition is that networks trained ... | 2020-03-26T15:43:10Z | The code can be found at https://github.com/clovaai/voxceleb_trainer | null | 10.21437/Interspeech.2020-1064 | null | null | null | null | null | null | null |
2,003.12039 | RAFT: Recurrent All-Pairs Field Transforms for Optical Flow | ['Zachary Teed', 'Jia Deng'] | ['cs.CV'] | We introduce Recurrent All-Pairs Field Transforms (RAFT), a new deep network
architecture for optical flow. RAFT extracts per-pixel features, builds
multi-scale 4D correlation volumes for all pairs of pixels, and iteratively
updates a flow field through a recurrent unit that performs lookups on the
correlation volumes.... | 2020-03-26T17:12:42Z | fixed a formatting issue, Eq 7. no change in content | null | null | null | null | null | null | null | null | null |
2,003.13016 | A Dataset of German Legal Documents for Named Entity Recognition | ['Elena Leitner', 'Georg Rehm', 'Julián Moreno-Schneider'] | ['cs.CL', 'cs.IR'] | We describe a dataset developed for Named Entity Recognition in German
federal court decisions. It consists of approx. 67,000 sentences with over 2
million tokens. The resource contains 54,000 manually annotated entities,
mapped to 19 fine-grained semantic classes: person, judge, lawyer, country,
city, street, landscap... | 2020-03-29T13:20:43Z | Proceedings of the 12th Language Resources and Evaluation Conference
(LREC 2020). To appear | null | null | A Dataset of German Legal Documents for Named Entity Recognition | ['Elena Leitner', 'Georg Rehm', 'J. Moreno-Schneider'] | 2,020 | International Conference on Language Resources and Evaluation | 51 | 39 | ['Computer Science'] |
2,003.13145 | Can AI help in screening Viral and COVID-19 pneumonia? | ['Muhammad E. H. Chowdhury', 'Tawsifur Rahman', 'Amith Khandakar', 'Rashid Mazhar', 'Muhammad Abdul Kadir', 'Zaid Bin Mahbub', 'Khandaker Reajul Islam', 'Muhammad Salman Khan', 'Atif Iqbal', 'Nasser Al-Emadi', 'Mamun Bin Ibne Reaz', 'T. I. Islam'] | ['cs.LG', 'cs.CV'] | Coronavirus disease (COVID-19) is a pandemic disease, which has already
caused thousands of causalities and infected several millions of people
worldwide. Any technological tool enabling rapid screening of the COVID-19
infection with high accuracy can be crucially helpful to healthcare
professionals. The main clinical ... | 2020-03-29T21:37:21Z | 12 pages, 9 Figures | IEEE Access 2020 | 10.1109/ACCESS.2020.3010287 | Can AI Help in Screening Viral and COVID-19 Pneumonia? | ['M. Chowdhury', 'Tawsifur Rahman', 'A. Khandakar', 'R. Mazhar', 'M. A. Kadir', 'Z. Mahbub', 'Khandakar R. Islam', 'Muhammad Salman Khan', 'A. Iqbal', 'N. Al-Emadi', 'M. Reaz'] | 2,020 | IEEE Access | 1,356 | 74 | ['Computer Science', 'Engineering'] |
2,003.1363 | TResNet: High Performance GPU-Dedicated Architecture | ['Tal Ridnik', 'Hussam Lawen', 'Asaf Noy', 'Emanuel Ben Baruch', 'Gilad Sharir', 'Itamar Friedman'] | ['cs.CV', 'cs.LG', 'eess.IV'] | Many deep learning models, developed in recent years, reach higher ImageNet
accuracy than ResNet50, with fewer or comparable FLOPS count. While FLOPs are
often seen as a proxy for network efficiency, when measuring actual GPU
training and inference throughput, vanilla ResNet50 is usually significantly
faster than its r... | 2020-03-30T17:04:47Z | 11 pages, 5 figures | null | null | null | null | null | null | null | null | null |
2,003.13678 | Designing Network Design Spaces | ['Ilija Radosavovic', 'Raj Prateek Kosaraju', 'Ross Girshick', 'Kaiming He', 'Piotr Dollár'] | ['cs.CV', 'cs.LG'] | In this work, we present a new network design paradigm. Our goal is to help
advance the understanding of network design and discover design principles that
generalize across settings. Instead of focusing on designing individual network
instances, we design network design spaces that parametrize populations of
networks.... | 2020-03-30T17:57:47Z | CVPR 2020 | null | null | null | null | null | null | null | null | null |
2,004.00033 | Give your Text Representation Models some Love: the Case for Basque | ['Rodrigo Agerri', 'Iñaki San Vicente', 'Jon Ander Campos', 'Ander Barrena', 'Xabier Saralegi', 'Aitor Soroa', 'Eneko Agirre'] | ['cs.CL'] | Word embeddings and pre-trained language models allow to build rich
representations of text and have enabled improvements across most NLP tasks.
Unfortunately they are very expensive to train, and many small companies and
research groups tend to use models that have been pre-trained and made
available by third parties,... | 2020-03-31T18:01:56Z | Accepted at LREC 2020; 8 pages, 7 tables | null | null | Give your Text Representation Models some Love: the Case for Basque | ['Rodrigo Agerri', 'Iñaki San Vicente', 'Jon Ander Campos', 'Ander Barrena', 'X. Saralegi', 'Aitor Soroa Etxabe', 'Eneko Agirre'] | 2,020 | International Conference on Language Resources and Evaluation | 63 | 24 | ['Computer Science'] |
2,004.00584 | Deep Entity Matching with Pre-Trained Language Models | ['Yuliang Li', 'Jinfeng Li', 'Yoshihiko Suhara', 'AnHai Doan', 'Wang-Chiew Tan'] | ['cs.DB', 'cs.CL'] | We present Ditto, a novel entity matching system based on pre-trained
Transformer-based language models. We fine-tune and cast EM as a sequence-pair
classification problem to leverage such models with a simple architecture. Our
experiments show that a straightforward application of language models such as
BERT, DistilB... | 2020-04-01T17:14:10Z | To appear in VLDB 2021 | null | 10.14778/3421424.3421431 | Deep entity matching with pre-trained language models | ['Yuliang Li', 'Jinfeng Li', 'Yoshihiko Suhara', 'A. Doan', 'W. Tan'] | 2,020 | Proceedings of the VLDB Endowment | 391 | 68 | ['Computer Science'] |
2,004.01092 | NUBES: A Corpus of Negation and Uncertainty in Spanish Clinical Texts | ['Salvador Lima', 'Naiara Perez', 'Montse Cuadros', 'German Rigau'] | ['cs.CL'] | This paper introduces the first version of the NUBes corpus (Negation and
Uncertainty annotations in Biomedical texts in Spanish). The corpus is part of
an on-going research and currently consists of 29,682 sentences obtained from
anonymised health records annotated with negation and uncertainty. The article
includes a... | 2020-04-02T15:51:31Z | Accepted at the Twelfth International Conference on Language
Resources and Evaluation (LREC 2020) | null | null | null | null | null | null | null | null | null |
2,004.01401 | XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training,
Understanding and Generation | ['Yaobo Liang', 'Nan Duan', 'Yeyun Gong', 'Ning Wu', 'Fenfei Guo', 'Weizhen Qi', 'Ming Gong', 'Linjun Shou', 'Daxin Jiang', 'Guihong Cao', 'Xiaodong Fan', 'Ruofei Zhang', 'Rahul Agrawal', 'Edward Cui', 'Sining Wei', 'Taroon Bharti', 'Ying Qiao', 'Jiun-Hung Chen', 'Winnie Wu', 'Shuguang Liu', 'Fan Yang', 'Daniel Campos'... | ['cs.CL'] | In this paper, we introduce XGLUE, a new benchmark dataset that can be used
to train large-scale cross-lingual pre-trained models using multilingual and
bilingual corpora and evaluate their performance across a diverse set of
cross-lingual tasks. Comparing to GLUE(Wang et al., 2019), which is labeled in
English for nat... | 2020-04-03T07:03:12Z | null | null | null | null | null | null | null | null | null | null |
2,004.01804 | Google Landmarks Dataset v2 -- A Large-Scale Benchmark for
Instance-Level Recognition and Retrieval | ['Tobias Weyand', 'Andre Araujo', 'Bingyi Cao', 'Jack Sim'] | ['cs.CV'] | While image retrieval and instance recognition techniques are progressing
rapidly, there is a need for challenging datasets to accurately measure their
performance -- while posing novel challenges that are relevant for practical
applications. We introduce the Google Landmarks Dataset v2 (GLDv2), a new
benchmark for lar... | 2020-04-03T22:52:17Z | CVPR20 camera-ready (oral) + appendices | null | null | Google Landmarks Dataset v2 – A Large-Scale Benchmark for Instance-Level Recognition and Retrieval | ['Tobias Weyand', 'A. Araújo', 'Bingyi Cao', 'Jack Sim'] | 2,020 | Computer Vision and Pattern Recognition | 373 | 70 | ['Computer Science'] |
2,004.02349 | TAPAS: Weakly Supervised Table Parsing via Pre-training | ['Jonathan Herzig', 'Paweł Krzysztof Nowak', 'Thomas Müller', 'Francesco Piccinno', 'Julian Martin Eisenschlos'] | ['cs.IR', 'cs.AI', 'cs.CL', 'cs.LG'] | Answering natural language questions over tables is usually seen as a
semantic parsing task. To alleviate the collection cost of full logical forms,
one popular approach focuses on weak supervision consisting of denotations
instead of logical forms. However, training semantic parsers from weak
supervision poses difficu... | 2020-04-05T23:18:37Z | Accepted to ACL 2020 | null | 10.18653/v1/2020.acl-main.398 | null | null | null | null | null | null | null |
2,004.02814 | Leveraging the Inherent Hierarchy of Vacancy Titles for Automated Job
Ontology Expansion | ['Jeroen Van Hautte', 'Vincent Schelstraete', 'Mikaël Wornoo'] | ['cs.CL', 'cs.LG'] | Machine learning plays an ever-bigger part in online recruitment, powering
intelligent matchmaking and job recommendations across many of the world's
largest job platforms. However, the main text is rarely enough to fully
understand a job posting: more often than not, much of the required information
is condensed into ... | 2020-04-06T16:55:41Z | Accepted to the Proceedings of the 6th International Workshop on
Computational Terminology (COMPUTERM 2020) | null | null | Leveraging the Inherent Hierarchy of Vacancy Titles for Automated Job Ontology Expansion | ['Jeroen Van Hautte', 'Vincent Schelstraete', 'Mikael Wornoo'] | 2,020 | COMPUTERM | 4 | 16 | ['Computer Science'] |
2,004.02967 | Evolving Normalization-Activation Layers | ['Hanxiao Liu', 'Andrew Brock', 'Karen Simonyan', 'Quoc V. Le'] | ['cs.LG', 'cs.CV', 'cs.NE', 'stat.ML'] | Normalization layers and activation functions are fundamental components in
deep networks and typically co-locate with each other. Here we propose to
design them using an automated approach. Instead of designing them separately,
we unify them into a single tensor-to-tensor computation graph, and evolve its
structure st... | 2020-04-06T19:52:48Z | null | null | null | null | null | null | null | null | null | null |
2,004.02984 | MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices | ['Zhiqing Sun', 'Hongkun Yu', 'Xiaodan Song', 'Renjie Liu', 'Yiming Yang', 'Denny Zhou'] | ['cs.CL', 'cs.LG'] | Natural Language Processing (NLP) has recently achieved great success by
using huge pre-trained models with hundreds of millions of parameters. However,
these models suffer from heavy model sizes and high latency such that they
cannot be deployed to resource-limited mobile devices. In this paper, we
propose MobileBERT ... | 2020-04-06T20:20:58Z | Accepted to ACL 2020 | null | null | MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices | ['Zhiqing Sun', 'Hongkun Yu', 'Xiaodan Song', 'Renjie Liu', 'Yiming Yang', 'Denny Zhou'] | 2,020 | Annual Meeting of the Association for Computational Linguistics | 820 | 66 | ['Computer Science'] |
2,004.03289 | KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language
Understanding | ['Jiyeon Ham', 'Yo Joong Choe', 'Kyubyong Park', 'Ilji Choi', 'Hyungjoon Soh'] | ['cs.CL'] | Natural language inference (NLI) and semantic textual similarity (STS) are
key tasks in natural language understanding (NLU). Although several benchmark
datasets for those tasks have been released in English and a few other
languages, there are no publicly available NLI or STS datasets in the Korean
language. Motivated... | 2020-04-07T11:49:15Z | Findings of EMNLP 2020. Datasets available at
https://github.com/kakaobrain/KorNLUDatasets | null | null | null | null | null | null | null | null | null |
2,004.03329 | MedDialog: Two Large-scale Medical Dialogue Datasets | ['Xuehai He', 'Shu Chen', 'Zeqian Ju', 'Xiangyu Dong', 'Hongchao Fang', 'Sicheng Wang', 'Yue Yang', 'Jiaqi Zeng', 'Ruisi Zhang', 'Ruoyu Zhang', 'Meng Zhou', 'Penghui Zhu', 'Pengtao Xie'] | ['cs.LG', 'cs.AI', 'cs.CL', 'stat.ML'] | Medical dialogue systems are promising in assisting in telemedicine to
increase access to healthcare services, improve the quality of patient care,
and reduce medical costs. To facilitate the research and development of medical
dialogue systems, we build two large-scale medical dialogue datasets:
MedDialog-EN and MedDi... | 2020-04-07T13:07:09Z | null | null | null | MedDialog: A Large-scale Medical Dialogue Dataset | ['Shu Chen', 'Zeqian Ju', 'Xiangyu Dong', 'Hongchao Fang', 'Sicheng Wang', 'Yue Yang', 'Jiaqi Zeng', 'Ruisi Zhang', 'Ruoyu Zhang', 'Meng Zhou', 'Penghui Zhu', 'Pengtao Xie'] | 2,020 | arXiv.org | 179 | 2 | ['Computer Science', 'Mathematics'] |
2,004.03659 | The Russian Drug Reaction Corpus and Neural Models for Drug Reactions
and Effectiveness Detection in User Reviews | ['Elena Tutubalina', 'Ilseyar Alimova', 'Zulfat Miftahutdinov', 'Andrey Sakhovskiy', 'Valentin Malykh', 'Sergey Nikolenko'] | ['cs.CL'] | The Russian Drug Reaction Corpus (RuDReC) is a new partially annotated corpus
of consumer reviews in Russian about pharmaceutical products for the detection
of health-related named entities and the effectiveness of pharmaceutical
products. The corpus itself consists of two parts, the raw one and the labelled
one. The r... | 2020-04-07T19:26:13Z | 9 pages, 9 tables, 4 figures | Bioinformatics, 2020 | 10.1093/bioinformatics/btaa675 | The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews | ['E. Tutubalina', 'I. Alimova', 'Z. Miftahutdinov', 'Andrey Sakhovskiy', 'Valentin Malykh', 'S. Nikolenko'] | 2,020 | Bioinform. | 44 | 26 | ['Computer Science', 'Medicine'] |
2,004.0372 | Byte Pair Encoding is Suboptimal for Language Model Pretraining | ['Kaj Bostrom', 'Greg Durrett'] | ['cs.CL', 'I.2.7'] | The success of pretrained transformer language models (LMs) in natural
language processing has led to a wide range of pretraining setups. In
particular, these models employ a variety of subword tokenization methods, most
notably byte-pair encoding (BPE) (Sennrich et al., 2016; Gage, 1994), the
WordPiece method (Schuste... | 2020-04-07T21:21:06Z | 5 pages, 3 figures. To be published in Findings of EMNLP 2020 | null | null | Byte Pair Encoding is Suboptimal for Language Model Pretraining | ['Kaj Bostrom', 'Greg Durrett'] | 2,020 | Findings | 215 | 28 | ['Computer Science'] |
2,004.04037 | DynaBERT: Dynamic BERT with Adaptive Width and Depth | ['Lu Hou', 'Zhiqi Huang', 'Lifeng Shang', 'Xin Jiang', 'Xiao Chen', 'Qun Liu'] | ['cs.CL', 'cs.LG'] | The pre-trained language models like BERT, though powerful in many natural
language processing tasks, are both computation and memory expensive. To
alleviate this problem, one approach is to compress them for specific tasks
before deployment. However, recent works on BERT compression usually compress
the large BERT mod... | 2020-04-08T15:06:28Z | NeurIPS-2020 (Spotlight) | null | null | null | null | null | null | null | null | null |
2,004.0427 | The Spotify Podcast Dataset | ['Ann Clifton', 'Aasish Pappu', 'Sravana Reddy', 'Yongze Yu', 'Jussi Karlgren', 'Ben Carterette', 'Rosie Jones'] | ['cs.CL'] | Podcasts are a relatively new form of audio media. Episodes appear on a
regular cadence, and come in many different formats and levels of formality.
They can be formal news journalism or conversational chat; fiction or
non-fiction. They are rapidly growing in popularity and yet have been
relatively little studied. As a... | 2020-04-08T21:25:00Z | 4 pages, 3 figures | null | null | null | null | null | null | null | null | null |
2,004.04315 | Large Arabic Twitter Dataset on COVID-19 | ['Sarah Alqurashi', 'Ahmad Alhindi', 'Eisa Alanazi'] | ['cs.SI', 'cs.CL'] | The 2019 coronavirus disease (COVID-19), emerged late December 2019 in China,
is now rapidly spreading across the globe. At the time of writing this paper,
the number of global confirmed cases has passed two millions and half with over
180,000 fatalities. Many countries have enforced strict social distancing
policies t... | 2020-04-09T01:07:12Z | null | null | null | null | null | null | null | null | null | null |
2,004.0441 | Att-HACK: An Expressive Speech Database with Social Attitudes | ['Clément Le Moine', 'Nicolas Obin'] | ['eess.AS'] | This paper presents Att-HACK, the first large database of acted speech with
social attitudes. Available databases of expressive speech are rare and very
often restricted to the primary emotions: anger, joy, sadness, fear. This
greatly limits the scope of the research on expressive speech. Besides, a
fundamental aspect ... | 2020-04-09T08:09:59Z | 5 pages, 5 figures | null | null | Att-HACK: An Expressive Speech Database with Social Attitudes | ['Clément Le Moine', 'Nicolas Obin'] | 2,020 | Proceedings of the International Conference on Speech Prosody | 19 | 35 | ['Engineering', 'Computer Science', 'Psychology'] |
2,004.0446 | PANDORA Talks: Personality and Demographics on Reddit | ['Matej Gjurković', 'Mladen Karan', 'Iva Vukojević', 'Mihaela Bošnjak', 'Jan Šnajder'] | ['cs.CL', 'cs.CY', 'cs.SI'] | Personality and demographics are important variables in social sciences,
while in NLP they can aid in interpretability and removal of societal biases.
However, datasets with both personality and demographic labels are scarce. To
address this, we present PANDORA, the first large-scale dataset of Reddit
comments labeled ... | 2020-04-09T10:08:05Z | Proceedings of the Ninth International Workshop on Natural Language
Processing for Social Media, NAACL 2021,
https://www.aclweb.org/anthology/2021.socialnlp-1.12 | null | null | null | null | null | null | null | null | null |
2,004.04696 | BLEURT: Learning Robust Metrics for Text Generation | ['Thibault Sellam', 'Dipanjan Das', 'Ankur P. Parikh'] | ['cs.CL'] | Text generation has made significant advances in the last few years. Yet,
evaluation metrics have lagged behind, as the most popular choices (e.g., BLEU
and ROUGE) may correlate poorly with human judgments. We propose BLEURT, a
learned evaluation metric based on BERT that can model human judgments with a
few thousand p... | 2020-04-09T17:26:52Z | Accepted at ACL 2020 | null | null | BLEURT: Learning Robust Metrics for Text Generation | ['Thibault Sellam', 'Dipanjan Das', 'Ankur P. Parikh'] | 2,020 | Annual Meeting of the Association for Computational Linguistics | 1,511 | 52 | ['Computer Science'] |
2,004.04906 | Dense Passage Retrieval for Open-Domain Question Answering | ['Vladimir Karpukhin', 'Barlas Oğuz', 'Sewon Min', 'Patrick Lewis', 'Ledell Wu', 'Sergey Edunov', 'Danqi Chen', 'Wen-tau Yih'] | ['cs.CL'] | Open-domain question answering relies on efficient passage retrieval to
select candidate contexts, where traditional sparse vector space models, such
as TF-IDF or BM25, are the de facto method. In this work, we show that
retrieval can be practically implemented using dense representations alone,
where embeddings are le... | 2020-04-10T04:53:17Z | EMNLP 2020 | null | null | null | null | null | null | null | null | null |
2,004.0515 | Longformer: The Long-Document Transformer | ['Iz Beltagy', 'Matthew E. Peters', 'Arman Cohan'] | ['cs.CL'] | Transformer-based models are unable to process long sequences due to their
self-attention operation, which scales quadratically with the sequence length.
To address this limitation, we introduce the Longformer with an attention
mechanism that scales linearly with sequence length, making it easy to process
documents of ... | 2020-04-10T17:54:09Z | Version 2 introduces the Longformer-Encoder-Decoder (LED) model | null | null | null | null | null | null | null | null | null |
2,004.05665 | Minimizing FLOPs to Learn Efficient Sparse Representations | ['Biswajit Paria', 'Chih-Kuan Yeh', 'Ian E. H. Yen', 'Ning Xu', 'Pradeep Ravikumar', 'Barnabás Póczos'] | ['cs.LG', 'stat.ML'] | Deep representation learning has become one of the most widely adopted
approaches for visual search, recommendation, and identification. Retrieval of
such representations from a large database is however computationally
challenging. Approximate methods based on learning compact representations,
have been widely explore... | 2020-04-12T18:09:02Z | Published at ICLR 2020 | null | null | Minimizing FLOPs to Learn Efficient Sparse Representations | ['Biswajit Paria', 'Chih-Kuan Yeh', 'N. Xu', 'B. Póczos', 'Pradeep Ravikumar', 'I. E. Yen'] | 2,020 | International Conference on Learning Representations | 69 | 90 | ['Computer Science', 'Mathematics'] |
2,004.05707 | VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classification | ['Zhibin Lu', 'Pan Du', 'Jian-Yun Nie'] | ['cs.CL', 'cs.LG', 'stat.ML', 'I.2.4; I.2.7'] | Much progress has been made recently on text classification with methods
based on neural networks. In particular, models using attention mechanism such
as BERT have shown to have the capability of capturing the contextual
information within a sentence or document. However, their ability of capturing
the global informat... | 2020-04-12T22:02:33Z | 12 pages, 2 figures | in J. M. Jose et al. (Eds.): ECIR 2020, LNCS 12035, pp.369-382,
2020 | null | VGCN-BERT: Augmenting BERT with Graph Embedding for Text Classification | ['Zhibin Lu', 'Pan Du', 'J. Nie'] | 2,020 | European Conference on Information Retrieval | 127 | 34 | ['Computer Science'] |
2,004.06364 | Polar nano-clusters in nominally paraelectric ceramics demonstrating
high microwave tunability for wireless communication | ['Hangfeng Zhang', 'Henry Giddens', 'Yajun Yue', 'Xinzhao Xu', 'Vicente Araullo-Peters', 'Vladimir Koval', 'Matteo Palma', 'Isaac Abrahams', 'Haixue Yan', 'Yang Hao'] | ['physics.app-ph', 'cond-mat.mtrl-sci'] | Dielectric materials, with high tunability at microwave frequencies, are key
components in the design of microwave communication systems. Dense
Ba0.6Sr0.4TiO3 (BST) ceramics, with different grain sizes, were prepared in
order to optimise the dielectric tunability via polar nano cluster effects.
Dielectric permittivity ... | 2020-04-14T09:00:33Z | 25pages, 6 figures | Journal of the European Ceramic Society,2020 | null | Polar nano-clusters in nominally paraelectric ceramics demonstrating high microwave tunability for wireless communication | ['Hangfeng Zhang', 'H. Giddens', 'Y. Yue', 'Xinzhao Xu', 'V. Araullo-Peters', 'V. Koval', 'M. Palma', 'I. Abrahams', 'Haixue Yan', 'Y. Hao'] | 2,020 | null | 37 | 45 | ['Materials Science', 'Physics'] |
2,004.06465 | Deep Learning Models for Multilingual Hate Speech Detection | ['Sai Saketh Aluru', 'Binny Mathew', 'Punyajoy Saha', 'Animesh Mukherjee'] | ['cs.SI', 'cs.CL'] | Hate speech detection is a challenging problem with most of the datasets
available in only one language: English. In this paper, we conduct a large
scale analysis of multilingual hate speech in 9 languages from 16 different
sources. We observe that in low resource setting, simple models such as LASER
embedding with log... | 2020-04-14T13:14:27Z | 16 pages, Accepted at ECML-PKDD 2020 | null | null | null | null | null | null | null | null | null |
2,004.06824 | Melanoma Detection using Adversarial Training and Deep Transfer Learning | ['Hasib Zunair', 'A. Ben Hamza'] | ['eess.IV', 'cs.CV'] | Skin lesion datasets consist predominantly of normal samples with only a
small percentage of abnormal ones, giving rise to the class imbalance problem.
Also, skin lesion images are largely similar in overall appearance owing to the
low inter-class variability. In this paper, we propose a two-stage framework
for automat... | 2020-04-14T22:46:20Z | Published in the Journal of Physics in Medicine and Biology (PMB),
April 2020. Codes at https://github.com/hasibzunair/adversarial-lesions | null | 10.1088/1361-6560/ab86d3 | null | null | null | null | null | null | null |
2,004.0687 | Coreferential Reasoning Learning for Language Representation | ['Deming Ye', 'Yankai Lin', 'Jiaju Du', 'Zhenghao Liu', 'Peng Li', 'Maosong Sun', 'Zhiyuan Liu'] | ['cs.CL'] | Language representation models such as BERT could effectively capture
contextual semantic information from plain text, and have been proved to
achieve promising results in lots of downstream NLP tasks with appropriate
fine-tuning. However, most existing language representation models cannot
explicitly handle coreferenc... | 2020-04-15T03:57:45Z | Accepted by EMNLP2020 | null | null | null | null | null | null | null | null | null |
2,004.07067 | Gestalt: a Stacking Ensemble for SQuAD2.0 | ['Mohamed El-Geish'] | ['cs.CL', 'cs.LG', 'stat.ML'] | We propose a deep-learning system -- for the SQuAD2.0 task -- that finds, or
indicates the lack of, a correct answer to a question in a context paragraph.
Our goal is to learn an ensemble of heterogeneous SQuAD2.0 models that, when
blended properly, outperforms the best model in the ensemble per se. We created
a stacki... | 2020-04-02T08:09:22Z | 11 pages, 7 figures, Stanford CS224n Natural Language Processing with
Deep Learning | null | null | null | null | null | null | null | null | null |
2,004.0718 | SPECTER: Document-level Representation Learning using Citation-informed
Transformers | ['Arman Cohan', 'Sergey Feldman', 'Iz Beltagy', 'Doug Downey', 'Daniel S. Weld'] | ['cs.CL'] | Representation learning is a critical ingredient for natural language
processing systems. Recent Transformer language models like BERT learn powerful
textual representations, but these models are targeted towards token- and
sentence-level training objectives and do not leverage information on
inter-document relatedness... | 2020-04-15T16:05:51Z | ACL 2020 | null | null | null | null | null | null | null | null | null |
2,004.07667 | Null It Out: Guarding Protected Attributes by Iterative Nullspace
Projection | ['Shauli Ravfogel', 'Yanai Elazar', 'Hila Gonen', 'Michael Twiton', 'Yoav Goldberg'] | ['cs.CL', 'cs.LG'] | The ability to control for the kinds of information encoded in neural
representation has a variety of use cases, especially in light of the challenge
of interpreting these models. We present Iterative Null-space Projection
(INLP), a novel method for removing information from neural representations.
Our method is based ... | 2020-04-16T14:02:50Z | Accepted as a long paper in ACL 2020 | null | null | null | null | null | null | null | null | null |
2,004.07807 | Classification Benchmarks for Under-resourced Bengali Language based on
Multichannel Convolutional-LSTM Network | ['Md. Rezaul Karim', 'Bharathi Raja Chakravarthi', 'John P. McCrae', 'Michael Cochez'] | ['cs.CL', 'cs.LG', 'stat.ML'] | Exponential growths of social media and micro-blogging sites not only provide
platforms for empowering freedom of expressions and individual voices but also
enables people to express anti-social behaviour like online harassment,
cyberbullying, and hate speech. Numerous works have been proposed to utilize
these data for... | 2020-04-11T22:17:04Z | This paper is under review in the Journal of Natural Language
Engineering | null | null | null | null | null | null | null | null | null |
2,004.08531 | MatchboxNet: 1D Time-Channel Separable Convolutional Neural Network
Architecture for Speech Commands Recognition | ['Somshubra Majumdar', 'Boris Ginsburg'] | ['eess.AS'] | We present an MatchboxNet - an end-to-end neural network for speech command
recognition. MatchboxNet is a deep residual network composed from blocks of 1D
time-channel separable convolution, batch-normalization, ReLU and dropout
layers. MatchboxNet reaches state-of-the-art accuracy on the Google Speech
Commands dataset... | 2020-04-18T05:49:27Z | null | null | 10.21437/Interspeech.2020-1058 | null | null | null | null | null | null | null |
2,004.08955 | ResNeSt: Split-Attention Networks | ['Hang Zhang', 'Chongruo Wu', 'Zhongyue Zhang', 'Yi Zhu', 'Haibin Lin', 'Zhi Zhang', 'Yue Sun', 'Tong He', 'Jonas Mueller', 'R. Manmatha', 'Mu Li', 'Alexander Smola'] | ['cs.CV'] | It is well known that featuremap attention and multi-path representation are
important for visual recognition. In this paper, we present a modularized
architecture, which applies the channel-wise attention on different network
branches to leverage their success in capturing cross-feature interactions and
learning diver... | 2020-04-19T20:40:31Z | null | null | null | null | null | null | null | null | null | null |
2,004.09015 | Incorporating External Knowledge through Pre-training for Natural
Language to Code Generation | ['Frank F. Xu', 'Zhengbao Jiang', 'Pengcheng Yin', 'Bogdan Vasilescu', 'Graham Neubig'] | ['cs.CL'] | Open-domain code generation aims to generate code in a general-purpose
programming language (such as Python) from natural language (NL) intents.
Motivated by the intuition that developers usually retrieve resources on the
web when writing code, we explore the effectiveness of incorporating two
varieties of external kno... | 2020-04-20T01:45:27Z | Accepted by ACL 2020 | null | null | Incorporating External Knowledge through Pre-training for Natural Language to Code Generation | ['Frank F. Xu', 'Zhengbao Jiang', 'Pengcheng Yin', 'Bogdan Vasilescu', 'Graham Neubig'] | 2,020 | Annual Meeting of the Association for Computational Linguistics | 84 | 32 | ['Computer Science'] |
2,004.09813 | Making Monolingual Sentence Embeddings Multilingual using Knowledge
Distillation | ['Nils Reimers', 'Iryna Gurevych'] | ['cs.CL'] | We present an easy and efficient method to extend existing sentence embedding
models to new languages. This allows to create multilingual versions from
previously monolingual models. The training is based on the idea that a
translated sentence should be mapped to the same location in the vector space
as the original se... | 2020-04-21T08:20:25Z | Accepted at EMNLP 2020 | null | null | Making Monolingual Sentence Embeddings Multilingual Using Knowledge Distillation | ['Nils Reimers', 'Iryna Gurevych'] | 2,020 | Conference on Empirical Methods in Natural Language Processing | 1,035 | 39 | ['Computer Science'] |
2,004.10404 | Logical Natural Language Generation from Open-Domain Tables | ['Wenhu Chen', 'Jianshu Chen', 'Yu Su', 'Zhiyu Chen', 'William Yang Wang'] | ['cs.CL', 'cs.AI'] | Neural natural language generation (NLG) models have recently shown
remarkable progress in fluency and coherence. However, existing studies on
neural NLG are primarily focused on surface-level realizations with limited
emphasis on logical inference, an important aspect of human thinking and
language. In this paper, we ... | 2020-04-22T06:03:10Z | Accepted to ACL 2020 as Long Paper | null | null | null | null | null | null | null | null | null |
2,004.10568 | Up or Down? Adaptive Rounding for Post-Training Quantization | ['Markus Nagel', 'Rana Ali Amjad', 'Mart van Baalen', 'Christos Louizos', 'Tijmen Blankevoort'] | ['cs.LG', 'cs.CV', 'stat.ML'] | When quantizing neural networks, assigning each floating-point weight to its
nearest fixed-point value is the predominant approach. We find that, perhaps
surprisingly, this is not the best we can do. In this paper, we propose
AdaRound, a better weight-rounding mechanism for post-training quantization
that adapts to the... | 2020-04-22T13:44:28Z | Published as a conference paper at ICML 2020 | null | null | null | null | null | null | null | null | null |
2,004.10934 | YOLOv4: Optimal Speed and Accuracy of Object Detection | ['Alexey Bochkovskiy', 'Chien-Yao Wang', 'Hong-Yuan Mark Liao'] | ['cs.CV', 'eess.IV'] | There are a huge number of features which are said to improve Convolutional
Neural Network (CNN) accuracy. Practical testing of combinations of such
features on large datasets, and theoretical justification of the result, is
required. Some features operate on certain models exclusively and for certain
problems exclusiv... | 2020-04-23T02:10:02Z | null | null | null | null | null | null | null | null | null | null |
2,004.10964 | Don't Stop Pretraining: Adapt Language Models to Domains and Tasks | ['Suchin Gururangan', 'Ana Marasović', 'Swabha Swayamdipta', 'Kyle Lo', 'Iz Beltagy', 'Doug Downey', 'Noah A. Smith'] | ['cs.CL', 'cs.LG'] | Language models pretrained on text from a wide variety of sources form the
foundation of today's NLP. In light of the success of these broad-coverage
models, we investigate whether it is still helpful to tailor a pretrained model
to the domain of a target task. We present a study across four domains
(biomedical and com... | 2020-04-23T04:21:19Z | ACL 2020 | null | null | Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks | ['Suchin Gururangan', 'Ana Marasović', 'Swabha Swayamdipta', 'Kyle Lo', 'Iz Beltagy', 'Doug Downey', 'Noah A. Smith'] | 2,020 | Annual Meeting of the Association for Computational Linguistics | 2,454 | 77 | ['Computer Science'] |
2,004.11362 | Supervised Contrastive Learning | ['Prannay Khosla', 'Piotr Teterwak', 'Chen Wang', 'Aaron Sarna', 'Yonglong Tian', 'Phillip Isola', 'Aaron Maschinot', 'Ce Liu', 'Dilip Krishnan'] | ['cs.LG', 'cs.CV', 'stat.ML'] | Contrastive learning applied to self-supervised representation learning has
seen a resurgence in recent years, leading to state of the art performance in
the unsupervised training of deep image models. Modern batch contrastive
approaches subsume or significantly outperform traditional contrastive losses
such as triplet... | 2020-04-23T17:58:56Z | null | null | null | null | null | null | null | null | null | null |
2,004.11579 | Probabilistically Masked Language Model Capable of Autoregressive
Generation in Arbitrary Word Order | ['Yi Liao', 'Xin Jiang', 'Qun Liu'] | ['cs.CL'] | Masked language model and autoregressive language model are two types of
language models. While pretrained masked language models such as BERT overwhelm
the line of natural language understanding (NLU) tasks, autoregressive language
models such as GPT are especially capable in natural language generation (NLG).
In this... | 2020-04-24T07:38:19Z | Accepted by ACL 2020 | null | null | Probabilistically Masked Language Model Capable of Autoregressive Generation in Arbitrary Word Order | ['Yi Liao', 'Xin Jiang', 'Qun Liu'] | 2,020 | Annual Meeting of the Association for Computational Linguistics | 40 | 34 | ['Computer Science'] |
2,004.11867 | Improving Massively Multilingual Neural Machine Translation and
Zero-Shot Translation | ['Biao Zhang', 'Philip Williams', 'Ivan Titov', 'Rico Sennrich'] | ['cs.CL'] | Massively multilingual models for neural machine translation (NMT) are
theoretically attractive, but often underperform bilingual models and deliver
poor zero-shot translations. In this paper, we explore ways to improve them. We
argue that multilingual NMT requires stronger modeling capacity to support
language pairs w... | 2020-04-24T17:21:32Z | ACL2020 | null | null | null | null | null | null | null | null | null |
2,004.12184 | A Named Entity Based Approach to Model Recipes | ['Nirav Diwan', 'Devansh Batra', 'Ganesh Bagler'] | ['cs.CL', 'cs.IR'] | Traditional cooking recipes follow a structure which can be modelled very
well if the rules and semantics of the different sections of the recipe text
are analyzed and represented accurately. We propose a structure that can
accurately represent the recipe as well as a pipeline to infer the best
representation of the re... | 2020-04-25T16:37:26Z | 36th IEEE International Conference on Data Engineering (ICDE 2020),
DECOR Workshop; 6 pages, 5 figures | null | null | A Named Entity Based Approach to Model Recipes | ['Nirav Diwan', 'Devansh Batra', 'Ganesh Bagler'] | 2,020 | 2020 IEEE 36th International Conference on Data Engineering Workshops (ICDEW) | 12 | 13 | ['Computer Science', 'Physics'] |
2,004.12832 | ColBERT: Efficient and Effective Passage Search via Contextualized Late
Interaction over BERT | ['Omar Khattab', 'Matei Zaharia'] | ['cs.IR', 'cs.CL'] | Recent progress in Natural Language Understanding (NLU) is driving fast-paced
advances in Information Retrieval (IR), largely owed to fine-tuning deep
language models (LMs) for document ranking. While remarkably effective, the
ranking models based on these LMs increase computational cost by orders of
magnitude over pri... | 2020-04-27T14:21:03Z | Accepted at SIGIR 2020 | null | null | ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT | ['O. Khattab', 'M. Zaharia'] | 2,020 | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval | 1,389 | 45 | ['Computer Science'] |
2,004.12992 | MakeItTalk: Speaker-Aware Talking-Head Animation | ['Yang Zhou', 'Xintong Han', 'Eli Shechtman', 'Jose Echevarria', 'Evangelos Kalogerakis', 'Dingzeyu Li'] | ['cs.CV', 'cs.GR'] | We present a method that generates expressive talking heads from a single
facial image with audio as the only input. In contrast to previous approaches
that attempt to learn direct mappings from audio to raw pixels or points for
creating talking faces, our method first disentangles the content and speaker
information i... | 2020-04-27T17:56:15Z | SIGGRAPH Asia 2020, 15 pages, 13 figures | null | 10.1145/3414685.3417774 | null | null | null | null | null | null | null |
2,004.13637 | Recipes for building an open-domain chatbot | ['Stephen Roller', 'Emily Dinan', 'Naman Goyal', 'Da Ju', 'Mary Williamson', 'Yinhan Liu', 'Jing Xu', 'Myle Ott', 'Kurt Shuster', 'Eric M. Smith', 'Y-Lan Boureau', 'Jason Weston'] | ['cs.CL', 'cs.AI'] | Building open-domain chatbots is a challenging area for machine learning
research. While prior work has shown that scaling neural models in the number
of parameters and the size of the data they are trained on gives improved
results, we show that other ingredients are important for a high-performing
chatbot. Good conve... | 2020-04-28T16:33:25Z | null | null | null | Recipes for Building an Open-Domain Chatbot | ['Stephen Roller', 'Emily Dinan', 'Naman Goyal', 'Da Ju', 'Mary Williamson', 'Yinhan Liu', 'Jing Xu', 'Myle Ott', 'Kurt Shuster', 'Eric Michael Smith', 'Y-Lan Boureau', 'J. Weston'] | 2,020 | Conference of the European Chapter of the Association for Computational Linguistics | 1,021 | 84 | ['Computer Science'] |
2,004.13796 | TextGAIL: Generative Adversarial Imitation Learning for Text Generation | ['Qingyang Wu', 'Lei Li', 'Zhou Yu'] | ['cs.CL', 'cs.LG'] | Generative Adversarial Networks (GANs) for text generation have recently
received many criticisms, as they perform worse than their MLE counterparts. We
suspect previous text GANs' inferior performance is due to the lack of a
reliable guiding signal in their discriminators. To address this problem, we
propose a generat... | 2020-04-07T00:24:35Z | AAAI 2021 | null | null | null | null | null | null | null | null | null |
2,004.13845 | DARE: Data Augmented Relation Extraction with GPT-2 | ['Yannis Papanikolaou', 'Andrea Pierleoni'] | ['cs.CL', 'cs.LG', 'stat.ML'] | Real-world Relation Extraction (RE) tasks are challenging to deal with,
either due to limited training data or class imbalance issues. In this work, we
present Data Augmented Relation Extraction(DARE), a simple method to augment
training data by properly fine-tuning GPT-2 to generate examples for specific
relation type... | 2020-04-06T14:38:36Z | null | null | null | null | null | null | null | null | null | null |
2,004.13922 | Revisiting Pre-Trained Models for Chinese Natural Language Processing | ['Yiming Cui', 'Wanxiang Che', 'Ting Liu', 'Bing Qin', 'Shijin Wang', 'Guoping Hu'] | ['cs.CL'] | Bidirectional Encoder Representations from Transformers (BERT) has shown
marvelous improvements across various NLP tasks, and consecutive variants have
been proposed to further improve the performance of the pre-trained language
models. In this paper, we target on revisiting Chinese pre-trained language
models to exami... | 2020-04-29T02:08:30Z | 12 pages, to appear at Findings of EMNLP 2020 | null | 10.18653/v1/2020.findings-emnlp.58 | null | null | null | null | null | null | null |
2,004.14166 | SpellGCN: Incorporating Phonological and Visual Similarities into
Language Models for Chinese Spelling Check | ['Xingyi Cheng', 'Weidi Xu', 'Kunlong Chen', 'Shaohua Jiang', 'Feng Wang', 'Taifeng Wang', 'Wei Chu', 'Yuan Qi'] | ['cs.CL'] | Chinese Spelling Check (CSC) is a task to detect and correct spelling errors
in Chinese natural language. Existing methods have made attempts to incorporate
the similarity knowledge between Chinese characters. However, they take the
similarity knowledge as either an external input resource or just heuristic
rules. This... | 2020-04-26T03:34:06Z | Accepted by ACL2020 | null | null | null | null | null | null | null | null | null |
2,004.14253 | GePpeTto Carves Italian into a Language Model | ['Lorenzo De Mattei', 'Michele Cafagna', "Felice Dell'Orletta", 'Malvina Nissim', 'Marco Guerini'] | ['cs.CL'] | In the last few years, pre-trained neural architectures have provided
impressive improvements across several NLP tasks. Still, generative language
models are available mainly for English. We develop GePpeTto, the first
generative language model for Italian, built using the GPT-2 architecture. We
provide a thorough anal... | 2020-04-29T15:02:01Z | null | null | null | null | null | null | null | null | null | null |
2,004.14255 | Efficient Document Re-Ranking for Transformers by Precomputing Term
Representations | ['Sean MacAvaney', 'Franco Maria Nardini', 'Raffaele Perego', 'Nicola Tonellotto', 'Nazli Goharian', 'Ophir Frieder'] | ['cs.IR'] | Deep pretrained transformer networks are effective at various ranking tasks,
such as question answering and ad-hoc document ranking. However, their
computational expenses deem them cost-prohibitive in practice. Our proposed
approach, called PreTTR (Precomputing Transformer Term Representations),
considerably reduces th... | 2020-04-29T15:04:22Z | Accepted at SIGIR 2020 (long) | null | 10.1145/3397271.3401093 | Efficient Document Re-Ranking for Transformers by Precomputing Term Representations | ['Sean MacAvaney', 'F. M. Nardini', 'R. Perego', 'N. Tonellotto', 'Nazli Goharian', 'O. Frieder'] | 2,020 | Annual International ACM SIGIR Conference on Research and Development in Information Retrieval | 120 | 53 | ['Computer Science'] |
2,004.149 | MLSUM: The Multilingual Summarization Corpus | ['Thomas Scialom', 'Paul-Alexis Dray', 'Sylvain Lamprier', 'Benjamin Piwowarski', 'Jacopo Staiano'] | ['cs.CL'] | We present MLSUM, the first large-scale MultiLingual SUMmarization dataset.
Obtained from online newspapers, it contains 1.5M+ article/summary pairs in
five different languages -- namely, French, German, Spanish, Russian, Turkish.
Together with English newspapers from the popular CNN/Daily mail dataset, the
collected d... | 2020-04-30T15:58:34Z | null | null | null | MLSUM: The Multilingual Summarization Corpus | ['Thomas Scialom', 'Paul-Alexis Dray', 'S. Lamprier', 'Benjamin Piwowarski', 'Jacopo Staiano'] | 2,020 | Conference on Empirical Methods in Natural Language Processing | 177 | 75 | ['Computer Science'] |
2,004.14963 | Data and Representation for Turkish Natural Language Inference | ['Emrah Budur', 'Rıza Özçelik', 'Tunga Güngör', 'Christopher Potts'] | ['cs.CL'] | Large annotated datasets in NLP are overwhelmingly in English. This is an
obstacle to progress in other languages. Unfortunately, obtaining new annotated
resources for each task in each language would be prohibitively expensive. At
the same time, commercial machine translation systems are now robust. Can we
leverage th... | 2020-04-30T17:12:52Z | Accepted to EMNLP 2020 | null | null | null | null | null | null | null | null | null |
2,004.15011 | TLDR: Extreme Summarization of Scientific Documents | ['Isabel Cachola', 'Kyle Lo', 'Arman Cohan', 'Daniel S. Weld'] | ['cs.CL'] | We introduce TLDR generation, a new form of extreme summarization, for
scientific papers. TLDR generation involves high source compression and
requires expert background knowledge and understanding of complex
domain-specific language. To facilitate study on this task, we introduce
SciTLDR, a new multi-target dataset of... | 2020-04-30T17:56:18Z | null | null | null | null | null | null | null | null | null | null |
2,005.00052 | MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer | ['Jonas Pfeiffer', 'Ivan Vulić', 'Iryna Gurevych', 'Sebastian Ruder'] | ['cs.CL'] | The main goal behind state-of-the-art pre-trained multilingual models such as
multilingual BERT and XLM-R is enabling and bootstrapping NLP applications in
low-resource languages through zero-shot or few-shot cross-lingual transfer.
However, due to limited model capacity, their transfer performance is the
weakest exact... | 2020-04-30T18:54:43Z | EMNLP 2020 | null | null | null | null | null | null | null | null | null |
2,005.00085 | AI4Bharat-IndicNLP Corpus: Monolingual Corpora and Word Embeddings for
Indic Languages | ['Anoop Kunchukuttan', 'Divyanshu Kakwani', 'Satish Golla', 'Gokul N. C.', 'Avik Bhattacharyya', 'Mitesh M. Khapra', 'Pratyush Kumar'] | ['cs.CL'] | We present the IndicNLP corpus, a large-scale, general-domain corpus
containing 2.7 billion words for 10 Indian languages from two language
families. We share pre-trained word embeddings trained on these corpora. We
create news article category classification datasets for 9 languages to
evaluate the embeddings. We show... | 2020-04-30T20:21:02Z | 7 pages, 8 tables,
https://github.com/ai4bharat-indicnlp/indicnlp_corpus | null | null | AI4Bharat-IndicNLP Corpus: Monolingual Corpora and Word Embeddings for Indic Languages | ['Anoop Kunchukuttan', 'Divyanshu Kakwani', 'S. Golla', 'C. GokulN.', 'Avik Bhattacharyya', 'Mitesh M. Khapra', 'Pratyush Kumar'] | 2,020 | arXiv.org | 83 | 27 | ['Computer Science'] |
2,005.00247 | AdapterFusion: Non-Destructive Task Composition for Transfer Learning | ['Jonas Pfeiffer', 'Aishwarya Kamath', 'Andreas Rücklé', 'Kyunghyun Cho', 'Iryna Gurevych'] | ['cs.CL'] | Sequential fine-tuning and multi-task learning are methods aiming to
incorporate knowledge from multiple tasks; however, they suffer from
catastrophic forgetting and difficulties in dataset balancing. To address these
shortcomings, we propose AdapterFusion, a new two stage learning algorithm that
leverages knowledge fr... | 2020-05-01T07:03:42Z | null | Proceedings of EACL 2021 | null | null | null | null | null | null | null | null |
2,005.00341 | Jukebox: A Generative Model for Music | ['Prafulla Dhariwal', 'Heewoo Jun', 'Christine Payne', 'Jong Wook Kim', 'Alec Radford', 'Ilya Sutskever'] | ['eess.AS', 'cs.LG', 'cs.SD', 'stat.ML'] | We introduce Jukebox, a model that generates music with singing in the raw
audio domain. We tackle the long context of raw audio using a multi-scale
VQ-VAE to compress it to discrete codes, and modeling those using
autoregressive Transformers. We show that the combined model at scale can
generate high-fidelity and dive... | 2020-04-30T09:02:45Z | null | null | null | null | null | null | null | null | null | null |
2,005.00547 | GoEmotions: A Dataset of Fine-Grained Emotions | ['Dorottya Demszky', 'Dana Movshovitz-Attias', 'Jeongwoo Ko', 'Alan Cowen', 'Gaurav Nemade', 'Sujith Ravi'] | ['cs.CL'] | Understanding emotion expressed in language has a wide range of applications,
from building empathetic chatbots to detecting harmful online behavior.
Advancement in this area can be improved using large-scale datasets with a
fine-grained typology, adaptable to multiple downstream tasks. We introduce
GoEmotions, the lar... | 2020-05-01T18:00:02Z | Accepted to ACL 2020 | null | null | GoEmotions: A Dataset of Fine-Grained Emotions | ['Dorottya Demszky', 'Dana Movshovitz-Attias', 'Jeongwoo Ko', 'Alan S. Cowen', 'Gaurav Nemade', 'Sujith Ravi'] | 2,020 | Annual Meeting of the Association for Computational Linguistics | 726 | 44 | ['Computer Science'] |
2,005.00628 | Intermediate-Task Transfer Learning with Pretrained Models for Natural
Language Understanding: When and Why Does It Work? | ['Yada Pruksachatkun', 'Jason Phang', 'Haokun Liu', 'Phu Mon Htut', 'Xiaoyi Zhang', 'Richard Yuanzhe Pang', 'Clara Vania', 'Katharina Kann', 'Samuel R. Bowman'] | ['cs.CL'] | While pretrained models such as BERT have shown large gains across natural
language understanding tasks, their performance can be improved by further
training the model on a data-rich intermediate task, before fine-tuning it on a
target task. However, it is still poorly understood when and why
intermediate-task trainin... | 2020-05-01T21:49:34Z | ACL 2020 | null | null | Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work? | ['Yada Pruksachatkun', 'Jason Phang', 'Haokun Liu', 'Phu Mon Htut', 'Xiaoyi Zhang', 'Richard Yuanzhe Pang', 'Clara Vania', 'Katharina Kann', 'Samuel R. Bowman'] | 2,020 | Annual Meeting of the Association for Computational Linguistics | 197 | 60 | ['Computer Science'] |
2,005.0063 | KLEJ: Comprehensive Benchmark for Polish Language Understanding | ['Piotr Rybak', 'Robert Mroczkowski', 'Janusz Tracz', 'Ireneusz Gawlik'] | ['cs.CL'] | In recent years, a series of Transformer-based models unlocked major
improvements in general natural language understanding (NLU) tasks. Such a fast
pace of research would not be possible without general NLU benchmarks, which
allow for a fair comparison of the proposed methods. However, such benchmarks
are available on... | 2020-05-01T21:55:40Z | null | null | null | null | null | null | null | null | null | null |
2,005.00661 | On Faithfulness and Factuality in Abstractive Summarization | ['Joshua Maynez', 'Shashi Narayan', 'Bernd Bohnet', 'Ryan McDonald'] | ['cs.CL'] | It is well known that the standard likelihood training and approximate
decoding objectives in neural text generation models lead to less human-like
responses for open-ended tasks such as language modeling and story generation.
In this paper we have analyzed limitations of these models for abstractive
document summariza... | 2020-05-02T00:09:16Z | ACL 2020, 14 pages | null | null | null | null | null | null | null | null | null |
2,005.01107 | Simplifying Paragraph-level Question Generation via Transformer Language
Models | ['Luis Enrico Lopez', 'Diane Kathryn Cruz', 'Jan Christian Blaise Cruz', 'Charibeth Cheng'] | ['cs.CL'] | Question generation (QG) is a natural language generation task where a model
is trained to ask questions corresponding to some input text. Most recent
approaches frame QG as a sequence-to-sequence problem and rely on additional
features and mechanisms to increase performance; however, these often increase
model complex... | 2020-05-03T14:57:24Z | To appear in PRICAI 2021. Formerly titled "Transformer-based
End-to-End Question Generation." | null | null | Simplifying Paragraph-Level Question Generation via Transformer Language Models | ['Luis Enrico Lopez', 'Diane Kathryn Cruz', 'Jan Christian Blaise Cruz', 'C. Cheng'] | 2,020 | Pacific Rim International Conference on Artificial Intelligence | 28 | 20 | ['Computer Science'] |
2,005.01643 | Offline Reinforcement Learning: Tutorial, Review, and Perspectives on
Open Problems | ['Sergey Levine', 'Aviral Kumar', 'George Tucker', 'Justin Fu'] | ['cs.LG', 'cs.AI', 'stat.ML'] | In this tutorial article, we aim to provide the reader with the conceptual
tools needed to get started on research on offline reinforcement learning
algorithms: reinforcement learning algorithms that utilize previously collected
data, without additional online data collection. Offline reinforcement learning
algorithms ... | 2020-05-04T17:00:15Z | null | null | null | null | null | null | null | null | null | null |
2,005.01996 | NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and
Results | ['Andreas Lugmayr', 'Martin Danelljan', 'Radu Timofte', 'Namhyuk Ahn', 'Dongwoon Bai', 'Jie Cai', 'Yun Cao', 'Junyang Chen', 'Kaihua Cheng', 'SeYoung Chun', 'Wei Deng', 'Mostafa El-Khamy', 'Chiu Man Ho', 'Xiaozhong Ji', 'Amin Kheradmand', 'Gwantae Kim', 'Hanseok Ko', 'Kanghyu Lee', 'Jungwon Lee', 'Hao Li', 'Ziluan Liu'... | ['eess.IV', 'cs.CV'] | This paper reviews the NTIRE 2020 challenge on real world super-resolution.
It focuses on the participating methods and final results. The challenge
addresses the real world setting, where paired true high and low-resolution
images are unavailable. For training, only one set of source input images is
therefore provided... | 2020-05-05T08:17:04Z | null | null | null | null | null | null | null | null | null | null |
2,005.02068 | Establishing Baselines for Text Classification in Low-Resource Languages | ['Jan Christian Blaise Cruz', 'Charibeth Cheng'] | ['cs.CL'] | While transformer-based finetuning techniques have proven effective in tasks
that involve low-resource, low-data environments, a lack of properly
established baselines and benchmark datasets make it hard to compare different
approaches that are aimed at tackling the low-resource setting. In this work,
we provide three ... | 2020-05-05T11:17:07Z | We release all our models, finetuning code, and data at
https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks | null | null | null | null | null | null | null | null | null |
2,005.02539 | Speak to your Parser: Interactive Text-to-SQL with Natural Language
Feedback | ['Ahmed Elgohary', 'Saghar Hosseini', 'Ahmed Hassan Awadallah'] | ['cs.CL'] | We study the task of semantic parse correction with natural language
feedback. Given a natural language utterance, most semantic parsing systems
pose the problem as one-shot translation where the utterance is mapped to a
corresponding logical form. In this paper, we investigate a more interactive
scenario where humans ... | 2020-05-05T23:58:09Z | ACL 2020 | null | null | null | null | null | null | null | null | null |
2,005.03521 | The Danish Gigaword Project | ['Leon Strømberg-Derczynski', 'Manuel R. Ciosici', 'Rebekah Baglini', 'Morten H. Christiansen', 'Jacob Aarup Dalsgaard', 'Riccardo Fusaroli', 'Peter Juel Henrichsen', 'Rasmus Hvingelby', 'Andreas Kirkedal', 'Alex Speed Kjeldsen', 'Claus Ladefoged', 'Finn Årup Nielsen', 'Malte Lau Petersen', 'Jonathan Hvithamar Rystrøm'... | ['cs.CL'] | Danish language technology has been hindered by a lack of broad-coverage
corpora at the scale modern NLP prefers. This paper describes the Danish
Gigaword Corpus, the result of a focused effort to provide a diverse and
freely-available one billion word corpus of Danish text. The Danish Gigaword
corpus covers a wide arr... | 2020-05-07T14:40:56Z | Identical to the NoDaLiDa 2021 version | null | null | The Danish Gigaword Corpus | ['Leon Derczynski', 'Manuel R. Ciosici', 'R. Baglini', 'Morten H. Christiansen', 'Jacob Aarup Dalsgaard', 'Riccardo Fusaroli', 'P. Henrichsen', 'Rasmus Hvingelby', 'Andreas Søeborg Kirkedal', 'Alex Speed Kjeldsen', 'Claus Ladefoged', 'F. Nielsen', 'Jens Madsen', 'M. Petersen', 'Jonathan H. Rystrøm', 'Daniel Varab'] | 2,020 | Nordic Conference of Computational Linguistics | 19 | 34 | ['Computer Science'] |
2,005.03754 | FEQA: A Question Answering Evaluation Framework for Faithfulness
Assessment in Abstractive Summarization | ['Esin Durmus', 'He He', 'Mona Diab'] | ['cs.CL'] | Neural abstractive summarization models are prone to generate content
inconsistent with the source document, i.e. unfaithful. Existing automatic
metrics do not capture such mistakes effectively. We tackle the problem of
evaluating faithfulness of a generated summary given its source document. We
first collected human a... | 2020-05-07T21:00:08Z | Accepted to ACL 2020 | null | 10.18653/v1/2020.acl-main.454 | null | null | null | null | null | null | null |
2,005.04132 | Asteroid: the PyTorch-based audio source separation toolkit for
researchers | ['Manuel Pariente', 'Samuele Cornell', 'Joris Cosentino', 'Sunit Sivasankaran', 'Efthymios Tzinis', 'Jens Heitkaemper', 'Michel Olvera', 'Fabian-Robert Stöter', 'Mathieu Hu', 'Juan M. Martín-Doñas', 'David Ditter', 'Ariel Frank', 'Antoine Deleforge', 'Emmanuel Vincent'] | ['eess.AS', 'cs.SD'] | This paper describes Asteroid, the PyTorch-based audio source separation
toolkit for researchers. Inspired by the most successful neural source
separation systems, it provides all neural building blocks required to build
such a system. To improve reproducibility, Kaldi-style recipes on common audio
source separation da... | 2020-05-08T16:18:34Z | Submitted to Interspeech 2020 | null | null | null | null | null | null | null | null | null |
2,005.05106 | Multi-band MelGAN: Faster Waveform Generation for High-Quality
Text-to-Speech | ['Geng Yang', 'Shan Yang', 'Kai Liu', 'Peng Fang', 'Wei Chen', 'Lei Xie'] | ['cs.SD', 'eess.AS'] | In this paper, we propose multi-band MelGAN, a much faster waveform
generation model targeting to high-quality text-to-speech. Specifically, we
improve the original MelGAN by the following aspects. First, we increase the
receptive field of the generator, which is proven to be beneficial to speech
generation. Second, we... | 2020-05-11T13:48:41Z | Submitted to Interspeech2020 | null | null | null | null | null | null | null | null | null |
2,005.05535 | DeepFaceLab: Integrated, flexible and extensible face-swapping framework | ['Ivan Perov', 'Daiheng Gao', 'Nikolay Chervoniy', 'Kunlin Liu', 'Sugasa Marangonda', 'Chris Umé', 'Dpfks', 'Carl Shift Facenheim', 'Luis RP', 'Jian Jiang', 'Sheng Zhang', 'Pingyu Wu', 'Bo Zhou', 'Weiming Zhang'] | ['cs.CV', 'cs.LG', 'cs.MM', 'eess.IV'] | Deepfake defense not only requires the research of detection but also
requires the efforts of generation methods. However, current deepfake methods
suffer the effects of obscure workflow and poor performance. To solve this
problem, we present DeepFaceLab, the current dominant deepfake framework for
face-swapping. It pr... | 2020-05-12T03:26:55Z | null | null | null | Deepfacelab: Integrated, flexible and extensible face-swapping framework | ['Kunlin Liu', 'Ivan Perov', 'Daiheng Gao', 'Nikolay Chervoniy', 'Wenbo Zhou', 'Weiming Zhang'] | 2,020 | Pattern Recognition | 232 | 46 | ['Computer Science', 'Engineering'] |
2,005.05635 | SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis | ['Hao Tian', 'Can Gao', 'Xinyan Xiao', 'Hao Liu', 'Bolei He', 'Hua Wu', 'Haifeng Wang', 'Feng Wu'] | ['cs.CL'] | Recently, sentiment analysis has seen remarkable advance with the help of
pre-training approaches. However, sentiment knowledge, such as sentiment words
and aspect-sentiment pairs, is ignored in the process of pre-training, despite
the fact that they are widely used in traditional sentiment analysis
approaches. In this... | 2020-05-12T09:23:32Z | Accepted by ACL2020 | null | null | null | null | null | null | null | null | null |
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