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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,009.01719 | Grounded Language Learning Fast and Slow | ['Felix Hill', 'Olivier Tieleman', 'Tamara von Glehn', 'Nathaniel Wong', 'Hamza Merzic', 'Stephen Clark'] | ['cs.CL', 'cs.AI'] | Recent work has shown that large text-based neural language models, trained
with conventional supervised learning objectives, acquire a surprising
propensity for few- and one-shot learning. Here, we show that an embodied agent
situated in a simulated 3D world, and endowed with a novel dual-coding external
memory, can e... | 2020-09-03T14:52:03Z | null | null | null | null | null | null | null | null | null | null |
2,009.02252 | KILT: a Benchmark for Knowledge Intensive Language Tasks | ['Fabio Petroni', 'Aleksandra Piktus', 'Angela Fan', 'Patrick Lewis', 'Majid Yazdani', 'Nicola De Cao', 'James Thorne', 'Yacine Jernite', 'Vladimir Karpukhin', 'Jean Maillard', 'Vassilis Plachouras', 'Tim Rocktäschel', 'Sebastian Riedel'] | ['cs.CL', 'cs.AI', 'cs.IR', 'cs.LG'] | Challenging problems such as open-domain question answering, fact checking,
slot filling and entity linking require access to large, external knowledge
sources. While some models do well on individual tasks, developing general
models is difficult as each task might require computationally expensive
indexing of custom k... | 2020-09-04T15:32:19Z | accepted at NAACL 2021 | null | null | null | null | null | null | null | null | null |
2,009.033 | Measuring Massive Multitask Language Understanding | ['Dan Hendrycks', 'Collin Burns', 'Steven Basart', 'Andy Zou', 'Mantas Mazeika', 'Dawn Song', 'Jacob Steinhardt'] | ['cs.CY', 'cs.AI', 'cs.CL', 'cs.LG'] | We propose a new test to measure a text model's multitask accuracy. The test
covers 57 tasks including elementary mathematics, US history, computer science,
law, and more. To attain high accuracy on this test, models must possess
extensive world knowledge and problem solving ability. We find that while most
recent mode... | 2020-09-07T17:59:25Z | ICLR 2021; the test and code is available at
https://github.com/hendrycks/test | null | null | Measuring Massive Multitask Language Understanding | ['Dan Hendrycks', 'Collin Burns', 'Steven Basart', 'Andy Zou', 'Mantas Mazeika', 'D. Song', 'J. Steinhardt'] | 2,020 | International Conference on Learning Representations | 4,587 | 35 | ['Computer Science'] |
2,009.04534 | Pay Attention when Required | ['Swetha Mandava', 'Szymon Migacz', 'Alex Fit Florea'] | ['cs.LG', 'cs.CL'] | Transformer-based models consist of interleaved feed-forward blocks - that
capture content meaning, and relatively more expensive self-attention blocks -
that capture context meaning. In this paper, we explored trade-offs and
ordering of the blocks to improve upon the current Transformer architecture and
proposed PAR T... | 2020-09-09T19:39:15Z | 9 pages, 5 figures, 7 tables | null | null | null | null | null | null | null | null | null |
2,009.05166 | FILTER: An Enhanced Fusion Method for Cross-lingual Language
Understanding | ['Yuwei Fang', 'Shuohang Wang', 'Zhe Gan', 'Siqi Sun', 'Jingjing Liu'] | ['cs.CL'] | Large-scale cross-lingual language models (LM), such as mBERT, Unicoder and
XLM, have achieved great success in cross-lingual representation learning.
However, when applied to zero-shot cross-lingual transfer tasks, most existing
methods use only single-language input for LM finetuning, without leveraging
the intrinsic... | 2020-09-10T22:42:15Z | Accepted to AAAI 2021; Top-1 Performance on XTREME
(https://sites.research.google/xtreme, September 8, 2020) and XGLUE
(https://microsoft.github.io/XGLUE, September 14, 2020) benchmark | null | null | FILTER: An Enhanced Fusion Method for Cross-lingual Language Understanding | ['Yuwei Fang', 'Shuohang Wang', 'Zhe Gan', 'S. Sun', 'Jingjing Liu'] | 2,020 | AAAI Conference on Artificial Intelligence | 58 | 33 | ['Computer Science'] |
2,009.05387 | IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural
Language Understanding | ['Bryan Wilie', 'Karissa Vincentio', 'Genta Indra Winata', 'Samuel Cahyawijaya', 'Xiaohong Li', 'Zhi Yuan Lim', 'Sidik Soleman', 'Rahmad Mahendra', 'Pascale Fung', 'Syafri Bahar', 'Ayu Purwarianti'] | ['cs.CL'] | Although Indonesian is known to be the fourth most frequently used language
over the internet, the research progress on this language in the natural
language processing (NLP) is slow-moving due to a lack of available resources.
In response, we introduce the first-ever vast resource for the training,
evaluating, and ben... | 2020-09-11T12:21:41Z | This paper will be presented in AACL-IJCNLP 2020 (with new results
and acknowledgment) | null | null | null | null | null | null | null | null | null |
2,009.06978 | Dialogue Response Ranking Training with Large-Scale Human Feedback Data | ['Xiang Gao', 'Yizhe Zhang', 'Michel Galley', 'Chris Brockett', 'Bill Dolan'] | ['cs.CL'] | Existing open-domain dialog models are generally trained to minimize the
perplexity of target human responses. However, some human replies are more
engaging than others, spawning more followup interactions. Current
conversational models are increasingly capable of producing turns that are
context-relevant, but in order... | 2020-09-15T10:50:05Z | Accepted to appear at EMNLP 2020 | null | null | Dialogue Response Ranking Training with Large-Scale Human Feedback Data | ['Xiang Gao', 'Yizhe Zhang', 'Michel Galley', 'Chris Brockett', 'Bill Dolan'] | 2,020 | Conference on Empirical Methods in Natural Language Processing | 107 | 35 | ['Computer Science'] |
2,009.07047 | Old Photo Restoration via Deep Latent Space Translation | ['Ziyu Wan', 'Bo Zhang', 'Dongdong Chen', 'Pan Zhang', 'Dong Chen', 'Jing Liao', 'Fang Wen'] | ['cs.CV', 'cs.GR'] | We propose to restore old photos that suffer from severe degradation through
a deep learning approach. Unlike conventional restoration tasks that can be
solved through supervised learning, the degradation in real photos is complex
and the domain gap between synthetic images and real old photos makes the
network fail to... | 2020-09-14T08:51:53Z | 15 pages. arXiv admin note: substantial text overlap with
arXiv:2004.09484 | null | null | Old Photo Restoration via Deep Latent Space Translation | ['Ziyu Wan', 'Bo Zhang', 'Dongdong Chen', 'P. Zhang', 'Dong Chen', 'Jing Liao', 'Fang Wen'] | 2,020 | IEEE Transactions on Pattern Analysis and Machine Intelligence | 68 | 88 | ['Computer Science', 'Medicine'] |
2,009.07185 | Critical Thinking for Language Models | ['Gregor Betz', 'Christian Voigt', 'Kyle Richardson'] | ['cs.CL', 'cs.AI'] | This paper takes a first step towards a critical thinking curriculum for
neural auto-regressive language models. We introduce a synthetic corpus of
deductively valid arguments, and generate artificial argumentative texts to
train and evaluate GPT-2. Significant transfer learning effects can be
observed: Training a mode... | 2020-09-15T15:49:19Z | null | null | null | null | null | null | null | null | null | null |
2,009.08366 | GraphCodeBERT: Pre-training Code Representations with Data Flow | ['Daya Guo', 'Shuo Ren', 'Shuai Lu', 'Zhangyin Feng', 'Duyu Tang', 'Shujie Liu', 'Long Zhou', 'Nan Duan', 'Alexey Svyatkovskiy', 'Shengyu Fu', 'Michele Tufano', 'Shao Kun Deng', 'Colin Clement', 'Dawn Drain', 'Neel Sundaresan', 'Jian Yin', 'Daxin Jiang', 'Ming Zhou'] | ['cs.SE', 'cs.CL'] | Pre-trained models for programming language have achieved dramatic empirical
improvements on a variety of code-related tasks such as code search, code
completion, code summarization, etc. However, existing pre-trained models
regard a code snippet as a sequence of tokens, while ignoring the inherent
structure of code, w... | 2020-09-17T15:25:56Z | Accepted by ICLR2021 | null | null | null | null | null | null | null | null | null |
2,009.0882 | FarsTail: A Persian Natural Language Inference Dataset | ['Hossein Amirkhani', 'Mohammad AzariJafari', 'Zohreh Pourjafari', 'Soroush Faridan-Jahromi', 'Zeinab Kouhkan', 'Azadeh Amirak'] | ['cs.CL'] | Natural language inference (NLI) is known as one of the central tasks in
natural language processing (NLP) which encapsulates many fundamental aspects
of language understanding. With the considerable achievements of data-hungry
deep learning methods in NLP tasks, a great amount of effort has been devoted
to develop mor... | 2020-09-18T13:04:04Z | null | Soft Computing (2023) | 10.1007/s00500-023-08959-3 | null | null | null | null | null | null | null |
2,009.09761 | DiffWave: A Versatile Diffusion Model for Audio Synthesis | ['Zhifeng Kong', 'Wei Ping', 'Jiaji Huang', 'Kexin Zhao', 'Bryan Catanzaro'] | ['eess.AS', 'cs.CL', 'cs.LG', 'cs.SD', 'stat.ML'] | In this work, we propose DiffWave, a versatile diffusion probabilistic model
for conditional and unconditional waveform generation. The model is
non-autoregressive, and converts the white noise signal into structured
waveform through a Markov chain with a constant number of steps at synthesis.
It is efficiently trained... | 2020-09-21T11:20:38Z | ICLR 2021 (oral) | null | null | null | null | null | null | null | null | null |
2,009.10053 | Latin BERT: A Contextual Language Model for Classical Philology | ['David Bamman', 'Patrick J. Burns'] | ['cs.CL'] | We present Latin BERT, a contextual language model for the Latin language,
trained on 642.7 million words from a variety of sources spanning the Classical
era to the 21st century. In a series of case studies, we illustrate the
affordances of this language-specific model both for work in natural language
processing for ... | 2020-09-21T17:47:44Z | null | null | null | Latin BERT: A Contextual Language Model for Classical Philology | ['David Bamman', 'P. Burns'] | 2,020 | arXiv.org | 79 | 61 | ['Computer Science'] |
2,009.10277 | Constructing interval variables via faceted Rasch measurement and
multitask deep learning: a hate speech application | ['Chris J. Kennedy', 'Geoff Bacon', 'Alexander Sahn', 'Claudia von Vacano'] | ['cs.CL', 'cs.LG', 'cs.SI', 'I.2.7'] | We propose a general method for measuring complex variables on a continuous,
interval spectrum by combining supervised deep learning with the Constructing
Measures approach to faceted Rasch item response theory (IRT). We decompose the
target construct, hate speech in our case, into multiple constituent components
that ... | 2020-09-22T02:15:05Z | 35 pages, 10 figures | null | null | null | null | null | null | null | null | null |
2,009.10297 | CodeBLEU: a Method for Automatic Evaluation of Code Synthesis | ['Shuo Ren', 'Daya Guo', 'Shuai Lu', 'Long Zhou', 'Shujie Liu', 'Duyu Tang', 'Neel Sundaresan', 'Ming Zhou', 'Ambrosio Blanco', 'Shuai Ma'] | ['cs.SE', 'cs.CL'] | Evaluation metrics play a vital role in the growth of an area as it defines
the standard of distinguishing between good and bad models. In the area of code
synthesis, the commonly used evaluation metric is BLEU or perfect accuracy, but
they are not suitable enough to evaluate codes, because BLEU is originally
designed ... | 2020-09-22T03:10:49Z | 8 pages, 6 figures | null | null | CodeBLEU: a Method for Automatic Evaluation of Code Synthesis | ['Shuo Ren', 'Daya Guo', 'Shuai Lu', 'Long Zhou', 'Shujie Liu', 'Duyu Tang', 'M. Zhou', 'Ambrosio Blanco', 'Shuai Ma'] | 2,020 | arXiv.org | 546 | 32 | ['Computer Science'] |
2,009.11462 | RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language
Models | ['Samuel Gehman', 'Suchin Gururangan', 'Maarten Sap', 'Yejin Choi', 'Noah A. Smith'] | ['cs.CL'] | 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 effectiveness of controllable text generation
algorithms at preventing su... | 2020-09-24T03:17:19Z | Findings in EMNLP 2020 | null | null | null | null | null | null | null | null | null |
2,009.11616 | N-LTP: An Open-source Neural Language Technology Platform for Chinese | ['Wanxiang Che', 'Yunlong Feng', 'Libo Qin', 'Ting Liu'] | ['cs.CL'] | We introduce \texttt{N-LTP}, an open-source neural language technology
platform supporting six fundamental Chinese NLP tasks: {lexical analysis}
(Chinese word segmentation, part-of-speech tagging, and named entity
recognition), {syntactic parsing} (dependency parsing), and {semantic parsing}
(semantic dependency parsin... | 2020-09-24T11:45:39Z | Accepted to appear in EMNLP 2021 (Demo) | null | null | N-LTP: An Open-source Neural Language Technology Platform for Chinese | ['Wanxiang Che', 'ylfeng', 'Libo Qin', 'Ting Liu'] | 2,020 | Conference on Empirical Methods in Natural Language Processing | 113 | 38 | ['Computer Science'] |
2,009.12756 | Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval | ['Wenhan Xiong', 'Xiang Lorraine Li', 'Srini Iyer', 'Jingfei Du', 'Patrick Lewis', 'William Yang Wang', 'Yashar Mehdad', 'Wen-tau Yih', 'Sebastian Riedel', 'Douwe Kiela', 'Barlas Oğuz'] | ['cs.CL'] | We propose a simple and efficient multi-hop dense retrieval approach for
answering complex open-domain questions, which achieves state-of-the-art
performance on two multi-hop datasets, HotpotQA and multi-evidence FEVER.
Contrary to previous work, our method does not require access to any
corpus-specific information, su... | 2020-09-27T06:12:29Z | null | null | null | Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval | ['Wenhan Xiong', 'Xiang Lorraine Li', 'Srini Iyer', 'Jingfei Du', 'Patrick Lewis', 'William Yang Wang', 'Yashar Mehdad', 'Wen-tau Yih', 'Sebastian Riedel', 'Douwe Kiela', 'Barlas Oğuz'] | 2,020 | International Conference on Learning Representations | 194 | 61 | ['Computer Science'] |
2,009.13013 | SPARTA: Efficient Open-Domain Question Answering via Sparse Transformer
Matching Retrieval | ['Tiancheng Zhao', 'Xiaopeng Lu', 'Kyusong Lee'] | ['cs.CL', 'cs.LG'] | We introduce SPARTA, a novel neural retrieval method that shows great promise
in performance, generalization, and interpretability for open-domain question
answering. Unlike many neural ranking methods that use dense vector nearest
neighbor search, SPARTA learns a sparse representation that can be efficiently
implement... | 2020-09-28T02:11:02Z | 11 pages | null | null | null | null | null | null | null | null | null |
2,009.13081 | What Disease does this Patient Have? A Large-scale Open Domain Question
Answering Dataset from Medical Exams | ['Di Jin', 'Eileen Pan', 'Nassim Oufattole', 'Wei-Hung Weng', 'Hanyi Fang', 'Peter Szolovits'] | ['cs.CL', 'cs.AI'] | Open domain question answering (OpenQA) tasks have been recently attracting
more and more attention from the natural language processing (NLP) community.
In this work, we present the first free-form multiple-choice OpenQA dataset for
solving medical problems, MedQA, collected from the professional medical board
exams. ... | 2020-09-28T05:07:51Z | Submitted to AAAI 2021 | null | null | What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams | ['Di Jin', 'Eileen Pan', 'Nassim Oufattole', 'W. Weng', 'Hanyi Fang', 'Peter Szolovits'] | 2,020 | Applied Sciences | 820 | 49 | ['Computer Science'] |
2,009.14725 | A Vietnamese Dataset for Evaluating Machine Reading Comprehension | ['Kiet Van Nguyen', 'Duc-Vu Nguyen', 'Anh Gia-Tuan Nguyen', 'Ngan Luu-Thuy Nguyen'] | ['cs.CL'] | Over 97 million people speak Vietnamese as their native language in the
world. However, there are few research studies on machine reading comprehension
(MRC) for Vietnamese, the task of understanding a text and answering questions
related to it. Due to the lack of benchmark datasets for Vietnamese, we present
the Vietn... | 2020-09-30T15:06:56Z | Accepted by The 28th International Conference on Computational
Linguistics (COLING 2020) | null | null | null | null | null | null | null | null | null |
2,009.14794 | Rethinking Attention with Performers | ['Krzysztof Choromanski', 'Valerii Likhosherstov', 'David Dohan', 'Xingyou Song', 'Andreea Gane', 'Tamas Sarlos', 'Peter Hawkins', 'Jared Davis', 'Afroz Mohiuddin', 'Lukasz Kaiser', 'David Belanger', 'Lucy Colwell', 'Adrian Weller'] | ['cs.LG', 'cs.CL', 'stat.ML'] | We introduce Performers, Transformer architectures which can estimate regular
(softmax) full-rank-attention Transformers with provable accuracy, but using
only linear (as opposed to quadratic) space and time complexity, without
relying on any priors such as sparsity or low-rankness. To approximate softmax
attention-ker... | 2020-09-30T17:09:09Z | Published as a conference paper + oral presentation at ICLR 2021. 38
pages. See
https://github.com/google-research/google-research/tree/master/protein_lm for
protein language model code, and
https://github.com/google-research/google-research/tree/master/performer for
Performer code. See
https://ai.googleblo... | null | null | null | null | null | null | null | null | null |
2,010.00133 | CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked
Language Models | ['Nikita Nangia', 'Clara Vania', 'Rasika Bhalerao', 'Samuel R. Bowman'] | ['cs.CL', 'cs.AI'] | Pretrained language models, especially masked language models (MLMs) have
seen success across many NLP tasks. However, there is ample evidence that they
use the cultural biases that are undoubtedly present in the corpora they are
trained on, implicitly creating harm with biased representations. To measure
some forms of... | 2020-09-30T22:38:40Z | EMNLP 2020 | null | null | null | null | null | null | null | null | null |
2,010.00571 | Understanding tables with intermediate pre-training | ['Julian Martin Eisenschlos', 'Syrine Krichene', 'Thomas Müller'] | ['cs.CL', 'cs.AI', 'cs.IR', 'cs.LG'] | Table entailment, the binary classification task of finding if a sentence is
supported or refuted by the content of a table, requires parsing language and
table structure as well as numerical and discrete reasoning. While there is
extensive work on textual entailment, table entailment is less well studied. We
adapt TAP... | 2020-10-01T17:43:27Z | Accepted to EMNLP Findings 2020 | null | null | Understanding tables with intermediate pre-training | ['Julian Martin Eisenschlos', 'Syrine Krichene', 'Thomas Müller'] | 2,020 | Findings | 121 | 58 | ['Computer Science'] |
2,010.00747 | Contrastive Learning of Medical Visual Representations from Paired
Images and Text | ['Yuhao Zhang', 'Hang Jiang', 'Yasuhide Miura', 'Christopher D. Manning', 'Curtis P. Langlotz'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Learning visual representations of medical images (e.g., X-rays) is core to
medical image understanding but its progress has been held back by the scarcity
of human annotations. Existing work commonly relies on fine-tuning weights
transferred from ImageNet pretraining, which is suboptimal due to drastically
different i... | 2020-10-02T02:10:18Z | First published in 2020. Accepted at Machine Learning for Healthcare
(MLHC) 2022 | null | null | Contrastive Learning of Medical Visual Representations from Paired Images and Text | ['Yuhao Zhang', 'Hang Jiang', 'Yasuhide Miura', 'Christopher D. Manning', 'C. Langlotz'] | 2,020 | Machine Learning in Health Care | 774 | 59 | ['Computer Science'] |
2,010.00904 | Autoregressive Entity Retrieval | ['Nicola De Cao', 'Gautier Izacard', 'Sebastian Riedel', 'Fabio Petroni'] | ['cs.CL', 'cs.IR', 'cs.LG', 'stat.ML'] | Entities are at the center of how we represent and aggregate knowledge. For
instance, Encyclopedias such as Wikipedia are structured by entities (e.g., one
per Wikipedia article). The ability to retrieve such entities given a query is
fundamental for knowledge-intensive tasks such as entity linking and
open-domain ques... | 2020-10-02T10:13:31Z | Accepted (spotlight) at International Conference on Learning
Representations (ICLR) 2021. Code at
https://github.com/facebookresearch/GENRE. 20 pages, 9 figures, 8 tables | null | null | null | null | null | null | null | null | null |
2,010.0098 | MultiCQA: Zero-Shot Transfer of Self-Supervised Text Matching Models on
a Massive Scale | ['Andreas Rücklé', 'Jonas Pfeiffer', 'Iryna Gurevych'] | ['cs.CL', 'cs.IR'] | We study the zero-shot transfer capabilities of text matching models on a
massive scale, by self-supervised training on 140 source domains from community
question answering forums in English. We investigate the model performances on
nine benchmarks of answer selection and question similarity tasks, and show
that all 14... | 2020-10-02T13:22:12Z | EMNLP-2020 | null | null | MultiCQA: Zero-Shot Transfer of Self-Supervised Text Matching Models on a Massive Scale | ['Andreas Rücklé', 'Jonas Pfeiffer', 'Iryna Gurevych'] | 2,020 | Conference on Empirical Methods in Natural Language Processing | 38 | 46 | ['Computer Science'] |
2,010.01057 | LUKE: Deep Contextualized Entity Representations with Entity-aware
Self-attention | ['Ikuya Yamada', 'Akari Asai', 'Hiroyuki Shindo', 'Hideaki Takeda', 'Yuji Matsumoto'] | ['cs.CL', 'cs.LG'] | Entity representations are useful in natural language tasks involving
entities. In this paper, we propose new pretrained contextualized
representations of words and entities based on the bidirectional transformer.
The proposed model treats words and entities in a given text as independent
tokens, and outputs contextual... | 2020-10-02T15:38:03Z | EMNLP 2020 | null | null | LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention | ['Ikuya Yamada', 'Akari Asai', 'Hiroyuki Shindo', 'Hideaki Takeda', 'Yuji Matsumoto'] | 2,020 | Conference on Empirical Methods in Natural Language Processing | 676 | 46 | ['Computer Science'] |
2,010.01073 | Efficient Image Super-Resolution Using Pixel Attention | ['Hengyuan Zhao', 'Xiangtao Kong', 'Jingwen He', 'Yu Qiao', 'Chao Dong'] | ['eess.IV', 'cs.CV'] | This work aims at designing a lightweight convolutional neural network for
image super resolution (SR). With simplicity bare in mind, we construct a
pretty concise and effective network with a newly proposed pixel attention
scheme. Pixel attention (PA) is similar as channel attention and spatial
attention in formulatio... | 2020-10-02T16:04:33Z | 17 pages, 5 figures, conference, accpeted by ECCVW (AIM2020 ESR
Challenge) | null | null | null | null | null | null | null | null | null |
2,010.01815 | High-resolution Piano Transcription with Pedals by Regressing Onset and
Offset Times | ['Qiuqiang Kong', 'Bochen Li', 'Xuchen Song', 'Yuan Wan', 'Yuxuan Wang'] | ['cs.SD', 'eess.AS'] | Automatic music transcription (AMT) is the task of transcribing audio
recordings into symbolic representations. Recently, neural network-based
methods have been applied to AMT, and have achieved state-of-the-art results.
However, many previous systems only detect the onset and offset of notes
frame-wise, so the transcr... | 2020-10-05T06:57:11Z | 12 pages | null | null | null | null | null | null | null | null | null |
2,010.02405 | Simple and Effective Few-Shot Named Entity Recognition with Structured
Nearest Neighbor Learning | ['Yi Yang', 'Arzoo Katiyar'] | ['cs.CL'] | We present a simple few-shot named entity recognition (NER) system based on
nearest neighbor learning and structured inference. Our system uses a
supervised NER model trained on the source domain, as a feature extractor.
Across several test domains, we show that a nearest neighbor classifier in this
feature-space is fa... | 2020-10-06T00:25:50Z | Accepted by EMNLP 2020 | null | null | Frustratingly Simple Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning | ['Yi Yang', 'Arzoo Katiyar'] | 2,020 | Conference on Empirical Methods in Natural Language Processing | 65 | 29 | ['Computer Science'] |
2,010.02502 | Denoising Diffusion Implicit Models | ['Jiaming Song', 'Chenlin Meng', 'Stefano Ermon'] | ['cs.LG', 'cs.CV'] | Denoising diffusion probabilistic models (DDPMs) have achieved high quality
image generation without adversarial training, yet they require simulating a
Markov chain for many steps to produce a sample. To accelerate sampling, we
present denoising diffusion implicit models (DDIMs), a more efficient class of
iterative im... | 2020-10-06T06:15:51Z | ICLR 2021; updated connections with ODEs at page 6, fixed some typos
in the proof | null | null | null | null | null | null | null | null | null |
2,010.02559 | LEGAL-BERT: The Muppets straight out of Law School | ['Ilias Chalkidis', 'Manos Fergadiotis', 'Prodromos Malakasiotis', 'Nikolaos Aletras', 'Ion Androutsopoulos'] | ['cs.CL'] | BERT has achieved impressive performance in several NLP tasks. However, there
has been limited investigation on its adaptation guidelines in specialised
domains. Here we focus on the legal domain, where we explore several approaches
for applying BERT models to downstream legal tasks, evaluating on multiple
datasets. Ou... | 2020-10-06T09:06:07Z | 5 pages, short paper in Findings of EMNLP 2020 | null | null | LEGAL-BERT: “Preparing the Muppets for Court’” | ['Ilias Chalkidis', 'Manos Fergadiotis', 'Prodromos Malakasiotis', 'Nikolaos Aletras', 'Ion Androutsopoulos'] | 2,020 | Findings | 265 | 32 | ['Computer Science'] |
2,010.02666 | Improving Efficient Neural Ranking Models with Cross-Architecture
Knowledge Distillation | ['Sebastian Hofstätter', 'Sophia Althammer', 'Michael Schröder', 'Mete Sertkan', 'Allan Hanbury'] | ['cs.IR'] | Retrieval and ranking models are the backbone of many applications such as
web search, open domain QA, or text-based recommender systems. The latency of
neural ranking models at query time is largely dependent on the architecture
and deliberate choices by their designers to trade-off effectiveness for higher
efficiency... | 2020-10-06T12:35:53Z | Updated paper with dense retrieval results and query-level analysis | null | null | null | null | null | null | null | null | null |
2,010.0281 | Swiss Parliaments Corpus, an Automatically Aligned Swiss German Speech
to Standard German Text Corpus | ['Michel Plüss', 'Lukas Neukom', 'Christian Scheller', 'Manfred Vogel'] | ['cs.CL', 'cs.LG'] | We present the Swiss Parliaments Corpus (SPC), an automatically aligned Swiss
German speech to Standard German text corpus. This first version of the corpus
is based on publicly available data of the Bernese cantonal parliament and
consists of 293 hours of data. It was created using a novel forced sentence
alignment pr... | 2020-10-06T15:18:21Z | 8 pages, 0 figures | null | null | null | null | null | null | null | null | null |
2,010.03295 | COMETA: A Corpus for Medical Entity Linking in the Social Media | ['Marco Basaldella', 'Fangyu Liu', 'Ehsan Shareghi', 'Nigel Collier'] | ['cs.CL'] | Whilst there has been growing progress in Entity Linking (EL) for general
language, existing datasets fail to address the complex nature of health
terminology in layman's language. Meanwhile, there is a growing need for
applications that can understand the public's voice in the health domain. To
address this we introdu... | 2020-10-07T09:16:45Z | Accepted to EMNLP 2020 | null | null | null | null | null | null | null | null | null |
2,010.03636 | MOCHA: A Dataset for Training and Evaluating Generative Reading
Comprehension Metrics | ['Anthony Chen', 'Gabriel Stanovsky', 'Sameer Singh', 'Matt Gardner'] | ['cs.CL', 'cs.LG'] | Posing reading comprehension as a generation problem provides a great deal of
flexibility, allowing for open-ended questions with few restrictions on
possible answers. However, progress is impeded by existing generation metrics,
which rely on token overlap and are agnostic to the nuances of reading
comprehension. To ad... | 2020-10-07T20:22:54Z | null | Proceedings of the 2020 Conference on Empirical Methods in Natural
Language Processing (EMNLP) | 10.18653/v1/2020.emnlp-main.528 | null | null | null | null | null | null | null |
2,010.04159 | Deformable DETR: Deformable Transformers for End-to-End Object Detection | ['Xizhou Zhu', 'Weijie Su', 'Lewei Lu', 'Bin Li', 'Xiaogang Wang', 'Jifeng Dai'] | ['cs.CV'] | DETR has been recently proposed to eliminate the need for many hand-designed
components in object detection while demonstrating good performance. However,
it suffers from slow convergence and limited feature spatial resolution, due to
the limitation of Transformer attention modules in processing image feature
maps. To ... | 2020-10-08T17:59:21Z | ICLR 2021 Oral | null | null | null | null | null | null | null | null | null |
2,010.04245 | Query-Key Normalization for Transformers | ['Alex Henry', 'Prudhvi Raj Dachapally', 'Shubham Pawar', 'Yuxuan Chen'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Low-resource language translation is a challenging but socially valuable NLP
task. Building on recent work adapting the Transformer's normalization to this
setting, we propose QKNorm, a normalization technique that modifies the
attention mechanism to make the softmax function less prone to arbitrary
saturation without ... | 2020-10-08T20:12:35Z | 8 pages, 2 figures, accepted at Findings of EMNLP 2020 | null | null | Query-Key Normalization for Transformers | ['Alex Henry', 'Prudhvi Raj Dachapally', 'S. Pawar', 'Yuxuan Chen'] | 2,020 | Findings | 91 | 41 | ['Computer Science'] |
2,010.04295 | Widget Captioning: Generating Natural Language Description for Mobile
User Interface Elements | ['Yang Li', 'Gang Li', 'Luheng He', 'Jingjie Zheng', 'Hong Li', 'Zhiwei Guan'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.HC'] | Natural language descriptions of user interface (UI) elements such as
alternative text are crucial for accessibility and language-based interaction
in general. Yet, these descriptions are constantly missing in mobile UIs. We
propose widget captioning, a novel task for automatically generating language
descriptions for ... | 2020-10-08T22:56:03Z | 16 pages, EMNLP 2020 | null | null | Widget Captioning: Generating Natural Language Description for Mobile User Interface Elements | ['Y. Li', 'Gang Li', 'Luheng He', 'Jingjie Zheng', 'Hong Li', 'Zhiwei Guan'] | 2,020 | Conference on Empirical Methods in Natural Language Processing | 110 | 39 | ['Computer Science'] |
2,010.04806 | AutoQA: From Databases To QA Semantic Parsers With Only Synthetic
Training Data | ['Silei Xu', 'Sina J. Semnani', 'Giovanni Campagna', 'Monica S. Lam'] | ['cs.CL'] | We propose AutoQA, a methodology and toolkit to generate semantic parsers
that answer questions on databases, with no manual effort. Given a database
schema and its data, AutoQA automatically generates a large set of high-quality
questions for training that covers different database operations. It uses
automatic paraph... | 2020-10-09T21:06:57Z | To appear in EMNLP 2020 | null | null | null | null | null | null | null | null | null |
2,010.05171 | fairseq S2T: Fast Speech-to-Text Modeling with fairseq | ['Changhan Wang', 'Yun Tang', 'Xutai Ma', 'Anne Wu', 'Sravya Popuri', 'Dmytro Okhonko', 'Juan Pino'] | ['cs.CL', 'eess.AS'] | We introduce fairseq S2T, a fairseq extension for speech-to-text (S2T)
modeling tasks such as end-to-end speech recognition and speech-to-text
translation. It follows fairseq's careful design for scalability and
extensibility. We provide end-to-end workflows from data pre-processing, model
training to offline (online) ... | 2020-10-11T05:36:54Z | Post-conference updates (accepted to AACL 2020 Demo) | null | null | null | null | null | null | null | null | null |
2,010.05338 | We Can Detect Your Bias: Predicting the Political Ideology of News
Articles | ['Ramy Baly', 'Giovanni Da San Martino', 'James Glass', 'Preslav Nakov'] | ['cs.CL'] | We explore the task of predicting the leading political ideology or bias of
news articles. First, we collect and release a large dataset of 34,737 articles
that were manually annotated for political ideology -left, center, or right-,
which is well-balanced across both topics and media. We further use a
challenging expe... | 2020-10-11T20:27:55Z | Political bias, bias in news, neural networks bias, adversarial
adaptation, triplet loss, transformers, recurrent neural networks | EMNLP-2020 | null | null | null | null | null | null | null | null |
2,010.05609 | Load What You Need: Smaller Versions of Multilingual BERT | ['Amine Abdaoui', 'Camille Pradel', 'Grégoire Sigel'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Pre-trained Transformer-based models are achieving state-of-the-art results
on a variety of Natural Language Processing data sets. However, the size of
these models is often a drawback for their deployment in real production
applications. In the case of multilingual models, most of the parameters are
located in the emb... | 2020-10-12T11:29:06Z | null | SustaiNLP / EMNLP 2020 | null | null | null | null | null | null | null | null |
2,010.05646 | HiFi-GAN: Generative Adversarial Networks for Efficient and High
Fidelity Speech Synthesis | ['Jungil Kong', 'Jaehyeon Kim', 'Jaekyoung Bae'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Several recent work on speech synthesis have employed generative adversarial
networks (GANs) to produce raw waveforms. Although such methods improve the
sampling efficiency and memory usage, their sample quality has not yet reached
that of autoregressive and flow-based generative models. In this work, we
propose HiFi-G... | 2020-10-12T12:33:43Z | NeurIPS 2020. Code available at https://github.com/jik876/hifi-gan | null | null | null | null | null | null | null | null | null |
2,010.057 | Reformulating Unsupervised Style Transfer as Paraphrase Generation | ['Kalpesh Krishna', 'John Wieting', 'Mohit Iyyer'] | ['cs.CL'] | Modern NLP defines the task of style transfer as modifying the style of a
given sentence without appreciably changing its semantics, which implies that
the outputs of style transfer systems should be paraphrases of their inputs.
However, many existing systems purportedly designed for style transfer
inherently warp the ... | 2020-10-12T13:31:01Z | EMNLP 2020 camera-ready (26 pages) | null | null | Reformulating Unsupervised Style Transfer as Paraphrase Generation | ['Kalpesh Krishna', 'J. Wieting', 'Mohit Iyyer'] | 2,020 | Conference on Empirical Methods in Natural Language Processing | 242 | 112 | ['Computer Science'] |
2,010.05987 | SLEDGE-Z: A Zero-Shot Baseline for COVID-19 Literature Search | ['Sean MacAvaney', 'Arman Cohan', 'Nazli Goharian'] | ['cs.CL', 'cs.IR'] | With worldwide concerns surrounding the Severe Acute Respiratory Syndrome
Coronavirus 2 (SARS-CoV-2), there is a rapidly growing body of scientific
literature on the virus. Clinicians, researchers, and policy-makers need to be
able to search these articles effectively. In this work, we present a zero-shot
ranking algor... | 2020-10-12T19:28:29Z | EMNLP 2020. This article draws heavily from arXiv:2005.02365 | null | null | null | null | null | null | null | null | null |
2,010.06 | MedICaT: A Dataset of Medical Images, Captions, and Textual References | ['Sanjay Subramanian', 'Lucy Lu Wang', 'Sachin Mehta', 'Ben Bogin', 'Madeleine van Zuylen', 'Sravanthi Parasa', 'Sameer Singh', 'Matt Gardner', 'Hannaneh Hajishirzi'] | ['cs.CV', 'cs.CL'] | Understanding the relationship between figures and text is key to scientific
document understanding. Medical figures in particular are quite complex, often
consisting of several subfigures (75% of figures in our dataset), with detailed
text describing their content. Previous work studying figures in scientific
papers f... | 2020-10-12T19:56:08Z | EMNLP-Findings 2020 | null | null | MedICaT: A Dataset of Medical Images, Captions, and Textual References | ['Sanjay Subramanian', 'Lucy Lu Wang', 'Sachin Mehta', 'Ben Bogin', 'Madeleine van Zuylen', 'S. Parasa', 'Sameer Singh', 'Matt Gardner', 'Hannaneh Hajishirzi'] | 2,020 | Findings | 74 | 24 | ['Computer Science'] |
2,010.06032 | Measuring and Reducing Gendered Correlations in Pre-trained Models | ['Kellie Webster', 'Xuezhi Wang', 'Ian Tenney', 'Alex Beutel', 'Emily Pitler', 'Ellie Pavlick', 'Jilin Chen', 'Ed Chi', 'Slav Petrov'] | ['cs.CL'] | Pre-trained models have revolutionized natural language understanding.
However, researchers have found they can encode artifacts undesired in many
applications, such as professions correlating with one gender more than
another. We explore such gendered correlations as a case study for how to
address unintended correlat... | 2020-10-12T21:15:29Z | null | null | null | null | null | null | null | null | null | null |
2,010.0606 | BioMegatron: Larger Biomedical Domain Language Model | ['Hoo-Chang Shin', 'Yang Zhang', 'Evelina Bakhturina', 'Raul Puri', 'Mostofa Patwary', 'Mohammad Shoeybi', 'Raghav Mani'] | ['cs.CL'] | There has been an influx of biomedical domain-specific language models,
showing language models pre-trained on biomedical text perform better on
biomedical domain benchmarks than those trained on general domain text corpora
such as Wikipedia and Books. Yet, most works do not study the factors affecting
each domain lang... | 2020-10-12T22:46:10Z | Accepted for publication at EMNLP 2020 | null | null | null | null | null | null | null | null | null |
2,010.06192 | Revisiting BFloat16 Training | ['Pedram Zamirai', 'Jian Zhang', 'Christopher R. Aberger', 'Christopher De Sa'] | ['cs.LG', 'stat.ML'] | State-of-the-art generic low-precision training algorithms use a mix of
16-bit and 32-bit precision, creating the folklore that 16-bit hardware compute
units alone are not enough to maximize model accuracy. As a result, deep
learning accelerators are forced to support both 16-bit and 32-bit
floating-point units (FPUs),... | 2020-10-13T05:38:07Z | null | null | null | null | null | null | null | null | null | null |
2,010.06354 | The Tatoeba Translation Challenge -- Realistic Data Sets for Low
Resource and Multilingual MT | ['Jörg Tiedemann'] | ['cs.CL'] | This paper describes the development of a new benchmark for machine
translation that provides training and test data for thousands of language
pairs covering over 500 languages and tools for creating state-of-the-art
translation models from that collection. The main goal is to trigger the
development of open translatio... | 2020-10-13T13:12:21Z | to be appear at the 5th Conference on Machine Translation (WMT20) | null | null | The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT | ['J. Tiedemann'] | 2,020 | Conference on Machine Translation | 171 | 16 | ['Computer Science'] |
2,010.06395 | Aspect-based Document Similarity for Research Papers | ['Malte Ostendorff', 'Terry Ruas', 'Till Blume', 'Bela Gipp', 'Georg Rehm'] | ['cs.CL', 'cs.IR'] | Traditional document similarity measures provide a coarse-grained distinction
between similar and dissimilar documents. Typically, they do not consider in
what aspects two documents are similar. This limits the granularity of
applications like recommender systems that rely on document similarity. In this
paper, we exte... | 2020-10-13T13:51:21Z | Accepted for publication at COLING 2020 | null | null | Aspect-based Document Similarity for Research Papers | ['Malte Ostendorff', 'Terry Ruas', 'Till Blume', 'Bela Gipp', 'Georg Rehm'] | 2,020 | International Conference on Computational Linguistics | 27 | 56 | ['Computer Science'] |
2,010.0729 | XPDNet for MRI Reconstruction: an application to the 2020 fastMRI
challenge | ['Zaccharie Ramzi', 'Philippe Ciuciu', 'Jean-Luc Starck'] | ['eess.IV', 'cs.CV', 'cs.LG', 'physics.med-ph', 'stat.ML'] | We present a new neural network, the XPDNet, for MRI reconstruction from
periodically under-sampled multi-coil data. We inform the design of this
network by taking best practices from MRI reconstruction and computer vision.
We show that this network can achieve state-of-the-art reconstruction results,
as shown by its r... | 2020-10-15T14:45:00Z | 8 pages, 3 figures, presented as an oral to the 2021 ISMRM conference | null | null | null | null | null | null | null | null | null |
2,010.07611 | Layer-adaptive sparsity for the Magnitude-based Pruning | ['Jaeho Lee', 'Sejun Park', 'Sangwoo Mo', 'Sungsoo Ahn', 'Jinwoo Shin'] | ['cs.LG'] | Recent discoveries on neural network pruning reveal that, with a carefully
chosen layerwise sparsity, a simple magnitude-based pruning achieves
state-of-the-art tradeoff between sparsity and performance. However, without a
clear consensus on "how to choose," the layerwise sparsities are mostly
selected algorithm-by-alg... | 2020-10-15T09:14:02Z | ICLR 2021. Changed title (previous ver: A deeper look at the
layerwise sparsity of magnitude-based pruning) | null | null | null | null | null | null | null | null | null |
2,010.0824 | Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for
Pairwise Sentence Scoring Tasks | ['Nandan Thakur', 'Nils Reimers', 'Johannes Daxenberger', 'Iryna Gurevych'] | ['cs.CL'] | There are two approaches for pairwise sentence scoring: Cross-encoders, which
perform full-attention over the input pair, and Bi-encoders, which map each
input independently to a dense vector space. While cross-encoders often achieve
higher performance, they are too slow for many practical use cases.
Bi-encoders, on th... | 2020-10-16T08:43:27Z | Accepted at NAACL 2021 | null | null | null | null | null | null | null | null | null |
2,010.08895 | Fourier Neural Operator for Parametric Partial Differential Equations | ['Zongyi Li', 'Nikola Kovachki', 'Kamyar Azizzadenesheli', 'Burigede Liu', 'Kaushik Bhattacharya', 'Andrew Stuart', 'Anima Anandkumar'] | ['cs.LG', 'cs.NA', 'math.NA'] | The classical development of neural networks has primarily focused on
learning mappings between finite-dimensional Euclidean spaces. Recently, this
has been generalized to neural operators that learn mappings between function
spaces. For partial differential equations (PDEs), neural operators directly
learn the mapping... | 2020-10-18T00:34:21Z | null | null | null | null | null | null | null | null | null | null |
2,010.09885 | ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular
Property Prediction | ['Seyone Chithrananda', 'Gabriel Grand', 'Bharath Ramsundar'] | ['cs.LG', 'cs.CL', 'physics.chem-ph', 'q-bio.BM', 'I.2.7; I.2.1; J.2; J.3'] | GNNs and chemical fingerprints are the predominant approaches to representing
molecules for property prediction. However, in NLP, transformers have become
the de-facto standard for representation learning thanks to their strong
downstream task transfer. In parallel, the software ecosystem around
transformers is maturin... | 2020-10-19T21:41:41Z | Submitted to NeurIPS 2020 ML for Molecules Workshop | null | null | null | null | null | null | null | null | null |
2,010.09931 | Smooth activations and reproducibility in deep networks | ['Gil I. Shamir', 'Dong Lin', 'Lorenzo Coviello'] | ['cs.LG', 'cs.NE', 'stat.ML'] | Deep networks are gradually penetrating almost every domain in our lives due
to their amazing success. However, with substantive performance accuracy
improvements comes the price of \emph{irreproducibility}. Two identical models,
trained on the exact same training dataset may exhibit large differences in
predictions on... | 2020-10-20T00:06:47Z | null | null | null | null | null | null | null | null | null | null |
2,010.10137 | PROP: Pre-training with Representative Words Prediction for Ad-hoc
Retrieval | ['Xinyu Ma', 'Jiafeng Guo', 'Ruqing Zhang', 'Yixing Fan', 'Xiang Ji', 'Xueqi Cheng'] | ['cs.IR', 'H.3.3'] | Recently pre-trained language representation models such as BERT have shown
great success when fine-tuned on downstream tasks including information
retrieval (IR). However, pre-training objectives tailored for ad-hoc retrieval
have not been well explored. In this paper, we propose Pre-training with
Representative wOrds... | 2020-10-20T09:04:56Z | Accepted by WSDM2021 | null | 10.1145/3437963.3441777 | PROP: Pre-training with Representative Words Prediction for Ad-hoc Retrieval | ['Xinyu Ma', 'Jiafeng Guo', 'Ruqing Zhang', 'Yixing Fan', 'Xiang Ji', 'Xueqi Cheng'] | 2,020 | Web Search and Data Mining | 98 | 50 | ['Computer Science'] |
2,010.10392 | CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary
Representations From Characters | ['Hicham El Boukkouri', 'Olivier Ferret', 'Thomas Lavergne', 'Hiroshi Noji', 'Pierre Zweigenbaum', 'Junichi Tsujii'] | ['cs.CL'] | Due to the compelling improvements brought by BERT, many recent
representation models adopted the Transformer architecture as their main
building block, consequently inheriting the wordpiece tokenization system
despite it not being intrinsically linked to the notion of Transformers. While
this system is thought to achi... | 2020-10-20T15:58:53Z | 13 pages, 8 figures and 3 tables. Accepted at COLING 2020 | null | null | null | null | null | null | null | null | null |
2,010.10499 | Optimal Subarchitecture Extraction For BERT | ['Adrian de Wynter', 'Daniel J. Perry'] | ['cs.CL', 'cs.LG'] | We extract an optimal subset of architectural parameters for the BERT
architecture from Devlin et al. (2018) by applying recent breakthroughs in
algorithms for neural architecture search. This optimal subset, which we refer
to as "Bort", is demonstrably smaller, having an effective (that is, not
counting the embedding ... | 2020-10-20T17:53:01Z | Preprint. Under review. Corrected typos on v2 | null | null | null | null | null | null | null | null | null |
2,010.10864 | A Short Note on the Kinetics-700-2020 Human Action Dataset | ['Lucas Smaira', 'João Carreira', 'Eric Noland', 'Ellen Clancy', 'Amy Wu', 'Andrew Zisserman'] | ['cs.CV', 'cs.LG'] | We describe the 2020 edition of the DeepMind Kinetics human action dataset,
which replenishes and extends the Kinetics-700 dataset. In this new version,
there are at least 700 video clips from different YouTube videos for each of
the 700 classes. This paper details the changes introduced for this new release
of the dat... | 2020-10-21T09:47:09Z | null | null | null | null | null | null | null | null | null | null |
2,010.10906 | German's Next Language Model | ['Branden Chan', 'Stefan Schweter', 'Timo Möller'] | ['cs.CL', 'cs.LG'] | In this work we present the experiments which lead to the creation of our
BERT and ELECTRA based German language models, GBERT and GELECTRA. By varying
the input training data, model size, and the presence of Whole Word Masking
(WWM) we were able to attain SoTA performance across a set of document
classification and na... | 2020-10-21T11:28:23Z | Accepted by COLING2020 | null | null | null | null | null | null | null | null | null |
2,010.10999 | Is Retriever Merely an Approximator of Reader? | ['Sohee Yang', 'Minjoon Seo'] | ['cs.CL'] | The state of the art in open-domain question answering (QA) relies on an
efficient retriever that drastically reduces the search space for the expensive
reader. A rather overlooked question in the community is the relationship
between the retriever and the reader, and in particular, if the whole purpose
of the retrieve... | 2020-10-21T13:40:15Z | null | null | null | null | null | null | null | null | null | null |
2,010.11125 | Beyond English-Centric Multilingual Machine Translation | ['Angela Fan', 'Shruti Bhosale', 'Holger Schwenk', 'Zhiyi Ma', 'Ahmed El-Kishky', 'Siddharth Goyal', 'Mandeep Baines', 'Onur Celebi', 'Guillaume Wenzek', 'Vishrav Chaudhary', 'Naman Goyal', 'Tom Birch', 'Vitaliy Liptchinsky', 'Sergey Edunov', 'Edouard Grave', 'Michael Auli', 'Armand Joulin'] | ['cs.CL', 'cs.LG'] | Existing work in translation demonstrated the potential of massively
multilingual machine translation by training a single model able to translate
between any pair of languages. However, much of this work is English-Centric by
training only on data which was translated from or to English. While this is
supported by lar... | 2020-10-21T17:01:23Z | null | null | null | null | null | null | null | null | null | null |
2,010.11386 | Distilling Dense Representations for Ranking using Tightly-Coupled
Teachers | ['Sheng-Chieh Lin', 'Jheng-Hong Yang', 'Jimmy Lin'] | ['cs.IR', 'cs.CL'] | We present an approach to ranking with dense representations that applies
knowledge distillation to improve the recently proposed late-interaction
ColBERT model. Specifically, we distill the knowledge from ColBERT's expressive
MaxSim operator for computing relevance scores into a simple dot product, thus
enabling singl... | 2020-10-22T02:26:01Z | null | null | null | Distilling Dense Representations for Ranking using Tightly-Coupled Teachers | ['Sheng-Chieh Lin', 'Jheng-Hong Yang', 'Jimmy J. Lin'] | 2,020 | arXiv.org | 122 | 28 | ['Computer Science'] |
2,010.1143 | Self-training and Pre-training are Complementary for Speech Recognition | ['Qiantong Xu', 'Alexei Baevski', 'Tatiana Likhomanenko', 'Paden Tomasello', 'Alexis Conneau', 'Ronan Collobert', 'Gabriel Synnaeve', 'Michael Auli'] | ['cs.LG', 'cs.SD', 'eess.AS'] | Self-training and unsupervised pre-training have emerged as effective
approaches to improve speech recognition systems using unlabeled data. However,
it is not clear whether they learn similar patterns or if they can be
effectively combined. In this paper, we show that pseudo-labeling and
pre-training with wav2vec 2.0 ... | 2020-10-22T04:15:37Z | null | null | null | Self-Training and Pre-Training are Complementary for Speech Recognition | ['Qiantong Xu', 'Alexei Baevski', 'Tatiana Likhomanenko', 'Paden Tomasello', 'Alexis Conneau', 'R. Collobert', 'Gabriel Synnaeve', 'Michael Auli'] | 2,020 | IEEE International Conference on Acoustics, Speech, and Signal Processing | 173 | 38 | ['Computer Science', 'Engineering'] |
2,010.11784 | Self-Alignment Pretraining for Biomedical Entity Representations | ['Fangyu Liu', 'Ehsan Shareghi', 'Zaiqiao Meng', 'Marco Basaldella', 'Nigel Collier'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Despite the widespread success of self-supervised learning via masked
language models (MLM), accurately capturing fine-grained semantic relationships
in the biomedical domain remains a challenge. This is of paramount importance
for entity-level tasks such as entity linking where the ability to model entity
relations (e... | 2020-10-22T14:59:57Z | NAACL 2021 camera-ready version | null | null | null | null | null | null | null | null | null |
2,010.11856 | XOR QA: Cross-lingual Open-Retrieval Question Answering | ['Akari Asai', 'Jungo Kasai', 'Jonathan H. Clark', 'Kenton Lee', 'Eunsol Choi', 'Hannaneh Hajishirzi'] | ['cs.CL'] | Multilingual question answering tasks typically assume answers exist in the
same language as the question. Yet in practice, many languages face both
information scarcity -- where languages have few reference articles -- and
information asymmetry -- where questions reference concepts from other
cultures. This work exten... | 2020-10-22T16:47:17Z | Published as a conference paper at NAACL-HLT 2021 (long) | null | null | null | null | null | null | null | null | null |
2,010.11929 | An Image is Worth 16x16 Words: Transformers for Image Recognition at
Scale | ['Alexey Dosovitskiy', 'Lucas Beyer', 'Alexander Kolesnikov', 'Dirk Weissenborn', 'Xiaohua Zhai', 'Thomas Unterthiner', 'Mostafa Dehghani', 'Matthias Minderer', 'Georg Heigold', 'Sylvain Gelly', 'Jakob Uszkoreit', 'Neil Houlsby'] | ['cs.CV', 'cs.AI', 'cs.LG'] | While the Transformer architecture has become the de-facto standard for
natural language processing tasks, its applications to computer vision remain
limited. In vision, attention is either applied in conjunction with
convolutional networks, or used to replace certain components of convolutional
networks while keeping ... | 2020-10-22T17:55:59Z | Fine-tuning code and pre-trained models are available at
https://github.com/google-research/vision_transformer. ICLR camera-ready
version with 2 small modifications: 1) Added a discussion of CLS vs GAP
classifier in the appendix, 2) Fixed an error in exaFLOPs computation in
Figure 5 and Table 6 (relative perfor... | null | null | null | null | null | null | null | null | null |
2,010.11934 | mT5: A massively multilingual pre-trained text-to-text transformer | ['Linting Xue', 'Noah Constant', 'Adam Roberts', 'Mihir Kale', 'Rami Al-Rfou', 'Aditya Siddhant', 'Aditya Barua', 'Colin Raffel'] | ['cs.CL'] | The recent "Text-to-Text Transfer Transformer" (T5) leveraged a unified
text-to-text format and scale to attain state-of-the-art results on a wide
variety of English-language NLP tasks. In this paper, we introduce mT5, a
multilingual variant of T5 that was pre-trained on a new Common Crawl-based
dataset covering 101 la... | 2020-10-22T17:58:14Z | null | null | null | mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer | ['Linting Xue', 'Noah Constant', 'Adam Roberts', 'Mihir Kale', 'Rami Al-Rfou', 'Aditya Siddhant', 'Aditya Barua', 'Colin Raffel'] | 2,020 | North American Chapter of the Association for Computational Linguistics | 2,570 | 55 | ['Computer Science'] |
2,010.12148 | ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling
for Natural Language Understanding | ['Dongling Xiao', 'Yu-Kun Li', 'Han Zhang', 'Yu Sun', 'Hao Tian', 'Hua Wu', 'Haifeng Wang'] | ['cs.CL', 'cs.LG'] | Coarse-grained linguistic information, such as named entities or phrases,
facilitates adequately representation learning in pre-training. Previous works
mainly focus on extending the objective of BERT's Masked Language Modeling
(MLM) from masking individual tokens to contiguous sequences of n tokens. We
argue that such... | 2020-10-23T03:42:20Z | Accepted by NAACL-HLT 2021. Codes will be released at
https://github.com/PaddlePaddle/ERNIE | null | null | null | null | null | null | null | null | null |
2,010.12321 | BARThez: a Skilled Pretrained French Sequence-to-Sequence Model | ['Moussa Kamal Eddine', 'Antoine J. -P. Tixier', 'Michalis Vazirgiannis'] | ['cs.CL'] | Inductive transfer learning has taken the entire NLP field by storm, with
models such as BERT and BART setting new state of the art on countless NLU
tasks. However, most of the available models and research have been conducted
for English. In this work, we introduce BARThez, the first large-scale
pretrained seq2seq mod... | 2020-10-23T11:57:33Z | More experiments and results, human evaluation, reorganization of
paper | null | null | null | null | null | null | null | null | null |
2,010.12421 | TweetEval: Unified Benchmark and Comparative Evaluation for Tweet
Classification | ['Francesco Barbieri', 'Jose Camacho-Collados', 'Leonardo Neves', 'Luis Espinosa-Anke'] | ['cs.CL', 'cs.SI'] | The experimental landscape in natural language processing for social media is
too fragmented. Each year, new shared tasks and datasets are proposed, ranging
from classics like sentiment analysis to irony detection or emoji prediction.
Therefore, it is unclear what the current state of the art is, as there is no
standar... | 2020-10-23T14:11:04Z | Findings of EMNLP 2020. TweetEval benchmark available at
https://github.com/cardiffnlp/tweeteval | null | null | null | null | null | null | null | null | null |
2,010.12725 | Compositional Generalization and Natural Language Variation: Can a
Semantic Parsing Approach Handle Both? | ['Peter Shaw', 'Ming-Wei Chang', 'Panupong Pasupat', 'Kristina Toutanova'] | ['cs.CL'] | Sequence-to-sequence models excel at handling natural language variation, but
have been shown to struggle with out-of-distribution compositional
generalization. This has motivated new specialized architectures with stronger
compositional biases, but most of these approaches have only been evaluated on
synthetically-gen... | 2020-10-24T00:38:27Z | ACL 2021 | null | null | null | null | null | null | null | null | null |
2,010.12821 | Rethinking embedding coupling in pre-trained language models | ['Hyung Won Chung', 'Thibault Févry', 'Henry Tsai', 'Melvin Johnson', 'Sebastian Ruder'] | ['cs.CL', 'cs.LG'] | We re-evaluate the standard practice of sharing weights between input and
output embeddings in state-of-the-art pre-trained language models. We show that
decoupled embeddings provide increased modeling flexibility, allowing us to
significantly improve the efficiency of parameter allocation in the input
embedding of mul... | 2020-10-24T07:43:00Z | null | null | null | Rethinking embedding coupling in pre-trained language models | ['Hyung Won Chung', 'Thibault Févry', 'Henry Tsai', 'Melvin Johnson', 'Sebastian Ruder'] | 2,020 | International Conference on Learning Representations | 143 | 73 | ['Computer Science'] |
2,010.12871 | Large Scale Legal Text Classification Using Transformer Models | ['Zein Shaheen', 'Gerhard Wohlgenannt', 'Erwin Filtz'] | ['cs.CL', 'cs.AI'] | Large multi-label text classification is a challenging Natural Language
Processing (NLP) problem that is concerned with text classification for
datasets with thousands of labels. We tackle this problem in the legal domain,
where datasets, such as JRC-Acquis and EURLEX57K labeled with the EuroVoc
vocabulary were created... | 2020-10-24T11:03:01Z | null | null | null | null | null | null | null | null | null | null |
2,010.13002 | Pre-trained Summarization Distillation | ['Sam Shleifer', 'Alexander M. Rush'] | ['cs.CL', 'cs.AI'] | Recent state-of-the-art approaches to summarization utilize large pre-trained
Transformer models. Distilling these models to smaller student models has
become critically important for practical use; however there are many different
distillation methods proposed by the NLP literature. Recent work on distilling
BERT for ... | 2020-10-24T23:15:43Z | null | null | null | Pre-trained Summarization Distillation | ['Sam Shleifer', 'Alexander M. Rush'] | 2,020 | arXiv.org | 103 | 32 | ['Computer Science'] |
2,010.13154 | Attention is All You Need in Speech Separation | ['Cem Subakan', 'Mirco Ravanelli', 'Samuele Cornell', 'Mirko Bronzi', 'Jianyuan Zhong'] | ['eess.AS', 'cs.LG', 'cs.SD', 'eess.SP'] | Recurrent Neural Networks (RNNs) have long been the dominant architecture in
sequence-to-sequence learning. RNNs, however, are inherently sequential models
that do not allow parallelization of their computations. Transformers are
emerging as a natural alternative to standard RNNs, replacing recurrent
computations with ... | 2020-10-25T16:28:54Z | Accepted to ICASSP 2021 | null | null | null | null | null | null | null | null | null |
2,010.13652 | Dutch Humor Detection by Generating Negative Examples | ['Thomas Winters', 'Pieter Delobelle'] | ['cs.CL', 'cs.AI', '68T50', 'I.2.7; I.2.6'] | Detecting if a text is humorous is a hard task to do computationally, as it
usually requires linguistic and common sense insights. In machine learning,
humor detection is usually modeled as a binary classification task, trained to
predict if the given text is a joke or another type of text. Rather than using
completely... | 2020-10-26T15:15:10Z | Accepted at the Proceedings of the 32st Benelux Conference on
Artificial Intelligence (BNAIC 2020) and the 29th Belgian Dutch Conference on
Machine Learning (Benelearn 2020) | null | null | Dutch Humor Detection by Generating Negative Examples | ['Thomas Winters', 'Pieter Delobelle'] | 2,020 | arXiv.org | 11 | 39 | ['Computer Science'] |
2,010.13886 | MarbleNet: Deep 1D Time-Channel Separable Convolutional Neural Network
for Voice Activity Detection | ['Fei Jia', 'Somshubra Majumdar', 'Boris Ginsburg'] | ['eess.AS', 'cs.SD'] | We present MarbleNet, an end-to-end neural network for Voice Activity
Detection (VAD). MarbleNet is a deep residual network composed from blocks of
1D time-channel separable convolution, batch-normalization, ReLU and dropout
layers. When compared to a state-of-the-art VAD model, MarbleNet is able to
achieve similar per... | 2020-10-26T20:26:05Z | Accepted to ICASSP 2021 | null | null | null | null | null | null | null | null | null |
2,010.13956 | Recent Developments on ESPnet Toolkit Boosted by Conformer | ['Pengcheng Guo', 'Florian Boyer', 'Xuankai Chang', 'Tomoki Hayashi', 'Yosuke Higuchi', 'Hirofumi Inaguma', 'Naoyuki Kamo', 'Chenda Li', 'Daniel Garcia-Romero', 'Jiatong Shi', 'Jing Shi', 'Shinji Watanabe', 'Kun Wei', 'Wangyou Zhang', 'Yuekai Zhang'] | ['eess.AS', 'cs.SD'] | In this study, we present recent developments on ESPnet: End-to-End Speech
Processing toolkit, which mainly involves a recently proposed architecture
called Conformer, Convolution-augmented Transformer. This paper shows the
results for a wide range of end-to-end speech processing applications, such as
automatic speech ... | 2020-10-26T23:49:23Z | null | null | null | null | null | null | null | null | null | null |
2,010.14235 | Multi-XScience: A Large-scale Dataset for Extreme Multi-document
Summarization of Scientific Articles | ['Yao Lu', 'Yue Dong', 'Laurent Charlin'] | ['cs.CL', 'cs.AI'] | Multi-document summarization is a challenging task for which there exists
little large-scale datasets. We propose Multi-XScience, a large-scale
multi-document summarization dataset created from scientific articles.
Multi-XScience introduces a challenging multi-document summarization task:
writing the related-work secti... | 2020-10-27T12:10:19Z | EMNLP 2020 | null | null | Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles | ['Yao Lu', 'Yue Dong', 'Laurent Charlin'] | 2,020 | Conference on Empirical Methods in Natural Language Processing | 120 | 31 | ['Computer Science'] |
2,010.14568 | Strongly Incremental Constituency Parsing with Graph Neural Networks | ['Kaiyu Yang', 'Jia Deng'] | ['cs.CL'] | Parsing sentences into syntax trees can benefit downstream applications in
NLP. Transition-based parsers build trees by executing actions in a state
transition system. They are computationally efficient, and can leverage machine
learning to predict actions based on partial trees. However, existing
transition-based pars... | 2020-10-27T19:19:38Z | Accepted to NeurIPS 2020 | null | null | null | null | null | null | null | null | null |
2,010.14819 | Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets | ['Kai Han', 'Yunhe Wang', 'Qiulin Zhang', 'Wei Zhang', 'Chunjing Xu', 'Tong Zhang'] | ['cs.CV'] | To obtain excellent deep neural architectures, a series of techniques are
carefully designed in EfficientNets. The giant formula for simultaneously
enlarging the resolution, depth and width provides us a Rubik's cube for neural
networks. So that we can find networks with high efficiency and excellent
performance by twi... | 2020-10-28T08:49:45Z | NeurIPS 2020 | null | null | null | null | null | null | null | null | null |
2,010.15052 | Image Representations Learned With Unsupervised Pre-Training Contain
Human-like Biases | ['Ryan Steed', 'Aylin Caliskan'] | ['cs.CY', 'cs.CV'] | Recent advances in machine learning leverage massive datasets of unlabeled
images from the web to learn general-purpose image representations for tasks
from image classification to face recognition. But do unsupervised computer
vision models automatically learn implicit patterns and embed social biases
that could have ... | 2020-10-28T15:55:49Z | 10 pages, 3 figures. Replaced example image completions of real
people with completions of artificial people | null | 10.1145/3442188.3445932 | null | null | null | null | null | null | null |
2,011.00677 | IndoLEM and IndoBERT: A Benchmark Dataset and Pre-trained Language Model
for Indonesian NLP | ['Fajri Koto', 'Afshin Rahimi', 'Jey Han Lau', 'Timothy Baldwin'] | ['cs.CL'] | Although the Indonesian language is spoken by almost 200 million people and
the 10th most spoken language in the world, it is under-represented in NLP
research. Previous work on Indonesian has been hampered by a lack of annotated
datasets, a sparsity of language resources, and a lack of resource
standardization. In thi... | 2020-11-02T01:54:56Z | Accepted at COLING 2020 - The 28th International Conference on
Computational Linguistics | null | null | IndoLEM and IndoBERT: A Benchmark Dataset and Pre-trained Language Model for Indonesian NLP | ['Fajri Koto', 'Afshin Rahimi', 'Jey Han Lau', 'Timothy Baldwin'] | 2,020 | International Conference on Computational Linguistics | 263 | 66 | ['Computer Science'] |
2,011.01513 | CharBERT: Character-aware Pre-trained Language Model | ['Wentao Ma', 'Yiming Cui', 'Chenglei Si', 'Ting Liu', 'Shijin Wang', 'Guoping Hu'] | ['cs.CL'] | Most pre-trained language models (PLMs) construct word representations at
subword level with Byte-Pair Encoding (BPE) or its variations, by which OOV
(out-of-vocab) words are almost avoidable. However, those methods split a word
into subword units and make the representation incomplete and fragile. In this
paper, we pr... | 2020-11-03T07:13:06Z | 12 pages, to appear at COLING 2020 | null | 10.18653/v1/2020.coling-main.4 | null | null | null | null | null | null | null |
2,011.03706 | ESPnet-se: end-to-end speech enhancement and separation toolkit designed
for asr integration | ['Chenda Li', 'Jing Shi', 'Wangyou Zhang', 'Aswin Shanmugam Subramanian', 'Xuankai Chang', 'Naoyuki Kamo', 'Moto Hira', 'Tomoki Hayashi', 'Christoph Boeddeker', 'Zhuo Chen', 'Shinji Watanabe'] | ['eess.AS', 'cs.SD'] | We present ESPnet-SE, which is designed for the quick development of speech
enhancement and speech separation systems in a single framework, along with the
optional downstream speech recognition module. ESPnet-SE is a new project which
integrates rich automatic speech recognition related models, resources and
systems t... | 2020-11-07T06:14:18Z | Accepted by SLT 2021 | null | 10.1109/SLT48900.2021.9383615 | ESPnet-SE: End-To-End Speech Enhancement and Separation Toolkit Designed for ASR Integration | ['Chenda Li', 'Jing Shi', 'Wangyou Zhang', 'A. Subramanian', 'Xuankai Chang', 'Naoyuki Kamo', 'Moto Hira', 'Tomoki Hayashi', 'Christoph Boeddeker', 'Zhuo Chen', 'Shinji Watanabe'] | 2,020 | Spoken Language Technology Workshop | 82 | 54 | ['Computer Science', 'Engineering'] |
2,011.04784 | EstBERT: A Pretrained Language-Specific BERT for Estonian | ['Hasan Tanvir', 'Claudia Kittask', 'Sandra Eiche', 'Kairit Sirts'] | ['cs.CL'] | This paper presents EstBERT, a large pretrained transformer-based
language-specific BERT model for Estonian. Recent work has evaluated
multilingual BERT models on Estonian tasks and found them to outperform the
baselines. Still, based on existing studies on other languages, a
language-specific BERT model is expected to... | 2020-11-09T21:33:53Z | NoDaLiDa 2021 | null | null | EstBERT: A Pretrained Language-Specific BERT for Estonian | ['Hasan Tanvir', 'Claudia Kittask', 'Kairit Sirts'] | 2,020 | Nordic Conference of Computational Linguistics | 37 | 26 | ['Computer Science'] |
2,011.06294 | Real-Time Intermediate Flow Estimation for Video Frame Interpolation | ['Zhewei Huang', 'Tianyuan Zhang', 'Wen Heng', 'Boxin Shi', 'Shuchang Zhou'] | ['cs.CV', 'cs.LG'] | Real-time video frame interpolation (VFI) is very useful in video processing,
media players, and display devices. We propose RIFE, a Real-time Intermediate
Flow Estimation algorithm for VFI. To realize a high-quality flow-based VFI
method, RIFE uses a neural network named IFNet that can estimate the
intermediate flows ... | 2020-11-12T10:12:06Z | Accepted to ECCV 2022 | null | null | null | null | null | null | null | null | null |
2,011.06993 | FLERT: Document-Level Features for Named Entity Recognition | ['Stefan Schweter', 'Alan Akbik'] | ['cs.CL'] | Current state-of-the-art approaches for named entity recognition (NER)
typically consider text at the sentence-level and thus do not model information
that crosses sentence boundaries. However, the use of transformer-based models
for NER offers natural options for capturing document-level features. In this
paper, we pe... | 2020-11-13T16:13:59Z | null | null | null | null | null | null | null | null | null | null |
2,011.09127 | 3D-FRONT: 3D Furnished Rooms with layOuts and semaNTics | ['Huan Fu', 'Bowen Cai', 'Lin Gao', 'Lingxiao Zhang', 'Jiaming Wang Cao Li', 'Zengqi Xun', 'Chengyue Sun', 'Rongfei Jia', 'Binqiang Zhao', 'Hao Zhang'] | ['cs.CV'] | We introduce 3D-FRONT (3D Furnished Rooms with layOuts and semaNTics), a new,
large-scale, and comprehensive repository of synthetic indoor scenes
highlighted by professionally designed layouts and a large number of rooms
populated by high-quality textured 3D models with style compatibility. From
layout semantics down ... | 2020-11-18T07:14:55Z | Project page:
https://tianchi.aliyun.com/specials/promotion/alibaba-3d-scene-dataset | null | null | 3D-FRONT: 3D Furnished Rooms with layOuts and semaNTics | ['Huan Fu', 'Bowen Cai', 'Lin Gao', 'Ling-Xiao Zhang', 'Cao Li', 'Zengqi Xun', 'Chengyue Sun', 'Yiyun Fei', 'Yu-qiong Zheng', 'Ying Li', 'Yi Liu', 'Peng Liu', 'Lin Ma', 'Le Weng', 'Xiaohang Hu', 'Xin Ma', 'Qian Qian', 'Rongfei Jia', 'Binqiang Zhao', 'H. Zhang'] | 2,020 | IEEE International Conference on Computer Vision | 276 | 50 | ['Computer Science'] |
2,011.09468 | Gradient Starvation: A Learning Proclivity in Neural Networks | ['Mohammad Pezeshki', 'Sékou-Oumar Kaba', 'Yoshua Bengio', 'Aaron Courville', 'Doina Precup', 'Guillaume Lajoie'] | ['cs.LG', 'math.DS', 'stat.ML'] | We identify and formalize a fundamental gradient descent phenomenon resulting
in a learning proclivity in over-parameterized neural networks. Gradient
Starvation arises when cross-entropy loss is minimized by capturing only a
subset of features relevant for the task, despite the presence of other
predictive features th... | 2020-11-18T18:52:08Z | Proceeding of NeurIPS 2021 | null | null | Gradient Starvation: A Learning Proclivity in Neural Networks | ['M. Pezeshki', 'S. Kaba', 'Y. Bengio', 'Aaron C. Courville', 'Doina Precup', 'Guillaume Lajoie'] | 2,020 | Neural Information Processing Systems | 269 | 117 | ['Computer Science', 'Mathematics'] |
2,011.1245 | Sparse R-CNN: End-to-End Object Detection with Learnable Proposals | ['Peize Sun', 'Rufeng Zhang', 'Yi Jiang', 'Tao Kong', 'Chenfeng Xu', 'Wei Zhan', 'Masayoshi Tomizuka', 'Lei Li', 'Zehuan Yuan', 'Changhu Wang', 'Ping Luo'] | ['cs.CV'] | We present Sparse R-CNN, a purely sparse method for object detection in
images. Existing works on object detection heavily rely on dense object
candidates, such as $k$ anchor boxes pre-defined on all grids of image feature
map of size $H\times W$. In our method, however, a fixed sparse set of learned
object proposals, ... | 2020-11-25T00:01:28Z | add test-dev; add crowdhuman | null | null | null | null | null | null | null | null | null |
2,011.13205 | SLURP: A Spoken Language Understanding Resource Package | ['Emanuele Bastianelli', 'Andrea Vanzo', 'Pawel Swietojanski', 'Verena Rieser'] | ['cs.CL', 'cs.LG'] | Spoken Language Understanding infers semantic meaning directly from audio
data, and thus promises to reduce error propagation and misunderstandings in
end-user applications. However, publicly available SLU resources are limited.
In this paper, we release SLURP, a new SLU package containing the following:
(1) A new chal... | 2020-11-26T09:58:20Z | Published at the 2020 Conference on Empirical Methods in Natural
Language Processing (EMNLP-2020) | null | null | null | null | null | null | null | null | null |
2,011.13456 | Score-Based Generative Modeling through Stochastic Differential
Equations | ['Yang Song', 'Jascha Sohl-Dickstein', 'Diederik P. Kingma', 'Abhishek Kumar', 'Stefano Ermon', 'Ben Poole'] | ['cs.LG', 'stat.ML'] | Creating noise from data is easy; creating data from noise is generative
modeling. We present a stochastic differential equation (SDE) that smoothly
transforms a complex data distribution to a known prior distribution by slowly
injecting noise, and a corresponding reverse-time SDE that transforms the prior
distribution... | 2020-11-26T19:39:10Z | ICLR 2021 (Oral) | null | null | null | null | null | null | null | null | null |
2,012.00413 | CPM: A Large-scale Generative Chinese Pre-trained Language Model | ['Zhengyan Zhang', 'Xu Han', 'Hao Zhou', 'Pei Ke', 'Yuxian Gu', 'Deming Ye', 'Yujia Qin', 'Yusheng Su', 'Haozhe Ji', 'Jian Guan', 'Fanchao Qi', 'Xiaozhi Wang', 'Yanan Zheng', 'Guoyang Zeng', 'Huanqi Cao', 'Shengqi Chen', 'Daixuan Li', 'Zhenbo Sun', 'Zhiyuan Liu', 'Minlie Huang', 'Wentao Han', 'Jie Tang', 'Juanzi Li', '... | ['cs.CL'] | Pre-trained Language Models (PLMs) have proven to be beneficial for various
downstream NLP tasks. Recently, GPT-3, with 175 billion parameters and 570GB
training data, drew a lot of attention due to the capacity of few-shot (even
zero-shot) learning. However, applying GPT-3 to address Chinese NLP tasks is
still challen... | 2020-12-01T11:32:56Z | null | null | null | CPM: A Large-scale Generative Chinese Pre-trained Language Model | ['Zhengyan Zhang', 'Xu Han', 'Hao Zhou', 'Pei Ke', 'Yuxian Gu', 'Deming Ye', 'Yujia Qin', 'Yusheng Su', 'Haozhe Ji', 'Jian Guan', 'Fanchao Qi', 'Xiaozhi Wang', 'Yanan Zheng', 'Guoyang Zeng', 'Huanqi Cao', 'S. Chen', 'Daixuan Li', 'Zhenbo Sun', 'Zhiyuan Liu', 'Minlie Huang', 'Wentao Han', 'Jie Tang', 'Juan-Zi Li', 'Xiao... | 2,020 | AI Open | 119 | 42 | ['Computer Science'] |
2,012.00483 | ClimaText: A Dataset for Climate Change Topic Detection | ['Francesco S. Varini', 'Jordan Boyd-Graber', 'Massimiliano Ciaramita', 'Markus Leippold'] | ['cs.CL', 'cs.AI'] | Climate change communication in the mass media and other textual sources may
affect and shape public perception. Extracting climate change information from
these sources is an important task, e.g., for filtering content and
e-discovery, sentiment analysis, automatic summarization, question-answering,
and fact-checking.... | 2020-12-01T13:42:37Z | Accepted for the Tackling Climate Change with Machine Learning
Workshop at NeurIPS 2020 | null | null | null | null | null | null | null | null | null |
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