Search Results for author:
Found 7 papers, 3 papers with code
Pseudo-Masked Language Models for Unified Language Model Pre-Training
We propose to pre-train a unified language model for both autoencoding and partially autoregressive language modeling tasks using a novel training procedure, referred to as a pseudo-masked language model (PMLM).
BEiT: BERT Pre-Training of Image Transformers
We first "tokenize" the original image into visual tokens.
Ranked #3 on
Document Layout Analysis
on PubLayNet val
A novel approach for multi-agent cooperative pursuit to capture grouped evaders
An approach of mobile multi-agent pursuit based on application of self-organizing feature map (SOFM) and along with that reinforcement learning based on agent group role membership function (AGRMF) model is proposed.
UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training
We propose to pre-train a unified language model for both autoencoding and partially autoregressive language modeling tasks using a novel training procedure, referred to as a pseudo-masked language model (PMLM).
Ranked #4 on
Question Generation
on SQuAD1.1
(using extra training data)
Inspecting Unification of Encoding and Matching with Transformer: A Case Study of Machine Reading Comprehension
Most machine reading comprehension (MRC) models separately handle encoding and matching with different network architectures.
Neural Melody Composition from Lyrics
In this paper, we study a novel task that learns to compose music from natural language.
Coalition formation for Multi-agent Pursuit based on Neural Network and AGRMF Model
An approach for coalition formation of multi-agent pursuit based on neural network and AGRMF model is proposed. This paper constructs a novel neural work called AGRMF-ANN which consists of feature extraction part and group generation part.
