research
∙
10/21/2020
ProphetNet-Ads: A Looking Ahead Strategy for Generative Retrieval Models in Sponsored Search Engine
In a sponsored search engine, generative retrieval models are recently p...
share
research
∙
10/16/2020
Unsupervised Extractive Summarization by Pre-training Hierarchical Transformers
Unsupervised extractive document summarization aims to select important ...
research
∙
10/15/2020
Neural Deepfake Detection with Factual Structure of Text
Deepfake detection, the task of automatically discriminating machine-gen...
research
∙
10/07/2020
Improving the Efficiency of Grammatical Error Correction with Erroneous Span Detection and Correction
We propose a novel language-independent approach to improve the efficien...
research
∙
10/04/2020
Tell Me How to Ask Again: Question Data Augmentation with Controllable Rewriting in Continuous Space
In this paper, we propose a novel data augmentation method, referred to ...
research
∙
09/22/2020
CodeBLEU: a Method for Automatic Evaluation of Code Synthesis
Evaluation metrics play a vital role in the growth of an area as it defi...
research
∙
09/17/2020
GraphCodeBERT: Pre-training Code Representations with Data Flow
Pre-trained models for programming language have achieved dramatic empir...
research
∙
08/13/2020
Continuous Speech Separation with Conformer
Continuous speech separation plays a vital role in complicated speech re...
research
∙
07/15/2020
InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training
In this work, we formulate cross-lingual language model pre-training as ...
research
∙
06/15/2020
Evidence-Aware Inferential Text Generation with Vector Quantised Variational AutoEncoder
Generating inferential texts about an event in different perspectives re...
research
∙
06/04/2020
M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-training
This paper presents a Multitask Multilingual Multimodal Pre-trained mode...
research
∙
06/01/2020
DocBank: A Benchmark Dataset for Document Layout Analysis
Document layout analysis usually relies on computer vision models to und...
research
∙
05/18/2020
MoBoAligner: a Neural Alignment Model for Non-autoregressive TTS with Monotonic Boundary Search
To speed up the inference of neural speech synthesis, non-autoregressive...
research
∙
05/12/2020
Document Modeling with Graph Attention Networks for Multi-grained Machine Reading Comprehension
Natural Questions is a new challenging machine reading comprehension ben...
research
∙
04/29/2020
Leveraging Declarative Knowledge in Text and First-Order Logic for Fine-Grained Propaganda Detection
We study the detection of propagandistic text fragments in news articles...
research
∙
04/28/2020
LogicalFactChecker: Leveraging Logical Operations for Fact Checking with Graph Module Network
Verifying the correctness of a textual statement requires not only seman...
research
∙
04/28/2020
Scheduled DropHead: A Regularization Method for Transformer Models
In this paper, we introduce DropHead, a structured dropout method specif...
research
∙
04/25/2020
A Heterogeneous Graph with Factual, Temporal and Logical Knowledge for Question Answering Over Dynamic Contexts
We study question answering over a dynamic textual environment. Although...
research
∙
04/21/2020
Curriculum Pre-training for End-to-End Speech Translation
End-to-end speech translation poses a heavy burden on the encoder, becau...
research
∙
04/12/2020
Pre-training Text Representations as Meta Learning
Pre-training text representations has recently been shown to significant...
research
∙
04/09/2020
MuTual: A Dataset for Multi-Turn Dialogue Reasoning
Non-task oriented dialogue systems have achieved great success in recent...
research
∙
04/07/2020
Inferential Text Generation with Multiple Knowledge Sources and Meta-Learning
We study the problem of generating inferential texts of events for a var...
research
∙
04/06/2020
At Which Level Should We Extract? An Empirical Study on Extractive Document Summarization
Extractive methods have proven to be very effective in automatic documen...
research
∙
04/06/2020
Learning to Summarize Passages: Mining Passage-Summary Pairs from Wikipedia Revision Histories
In this paper, we propose a method for automatically constructing a pass...
research
∙
04/04/2020
STEP: Sequence-to-Sequence Transformer Pre-training for Document Summarization
Abstractive summarization aims to rewrite a long document to its shorter...
research
∙
04/03/2020
XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation
In this paper, we introduce XGLUE, a new benchmark dataset to train larg...
research
∙
03/03/2020
XGPT: Cross-modal Generative Pre-Training for Image Captioning
While many BERT-based cross-modal pre-trained models produce excellent r...
research
∙
02/28/2020
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training
We propose to pre-train a unified language model for both autoencoding a...
research
∙
02/25/2020
MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers
Pre-trained language models (e.g., BERT (Devlin et al., 2018) and its va...
research
∙
02/19/2020
CodeBERT: A Pre-Trained Model for Programming and Natural Languages
We present CodeBERT, a bimodal pre-trained model for programming languag...
research
∙
02/15/2020
UniViLM: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation
We propose UniViLM: a Unified Video and Language pre-training Model for ...
research
∙
02/07/2020
BERT-of-Theseus: Compressing BERT by Progressive Module Replacing
In this paper, we propose a novel model compression approach to effectiv...
research
∙
02/05/2020
K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters
We study the problem of injecting knowledge into large pre-trained model...
research
∙
01/31/2020
Self-Adversarial Learning with Comparative Discrimination for Text Generation
Conventional Generative Adversarial Networks (GANs) for text generation ...
research
∙
01/13/2020
ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training
In this paper, we present a new sequence-to-sequence pre-training model ...
research
∙
01/04/2020
Multi-Agent Interactions Modeling with Correlated Policies
In multi-agent systems, complex interacting behaviors arise due to the h...
research
∙
12/31/2019
LayoutLM: Pre-training of Text and Layout for Document Image Understanding
Pre-training techniques have been verified successfully in a variety of ...
research
∙
12/06/2019
Semantic Mask for Transformer based End-to-End Speech Recognition
Attention-based encoder-decoder model has achieved impressive results fo...
research
∙
11/07/2019
Improving Grammatical Error Correction with Machine Translation Pairs
We propose a novel data synthesis method to generate diverse error-corre...
research
∙
10/07/2019
Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching
Improving the efficiency of dispatching orders to vehicles is a research...
research
∙
09/17/2019
Bridging the Gap between Pre-Training and Fine-Tuning for End-to-End Speech Translation
End-to-end speech translation, a hot topic in recent years, aims to tran...
research
∙
09/13/2019
Sequence-to-sequence Pre-training with Data Augmentation for Sentence Rewriting
We study sequence-to-sequence (seq2seq) pre-training with data augmentat...
research
∙
09/10/2019
Signal Instructed Coordination in Team Competition
Most existing models of multi-agent reinforcement learning (MARL) adopt ...
research
∙
09/10/2019
Signal Instructed Coordination in Cooperative Multi-agent Reinforcement Learning
In many real-world problems, a team of agents need to collaborate to max...
research
∙
09/09/2019
Reasoning Over Semantic-Level Graph for Fact Checking
We study fact-checking in this paper, which aims to verify a textual cla...
research
∙
09/03/2019
Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks
We present Unicoder, a universal language encoder that is insensitive to...
research
∙
08/31/2019
Explicit Cross-lingual Pre-training for Unsupervised Machine Translation
Pre-training has proven to be effective in unsupervised machine translat...
research
∙
08/16/2019
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training
We propose Unicoder-VL, a universal encoder that aims to learn joint rep...
research
∙
07/02/2019
Pathologist-Level Grading of Prostate Biopsies with Artificial Intelligence
Background: An increasing volume of prostate biopsies and a world-wide s...
research
∙
06/24/2019
