b'Zhouhan Lin'

research

∙ 06/08/2023

Learning A Foundation Language Model for Geoscience Knowledge Understanding and Utilization

Large language models (LLMs)have achieved great success in general domai...

0 Cheng Deng, et al. ∙

research

∙ 05/24/2023

Fourier Transformer: Fast Long Range Modeling by Removing Sequence Redundancy with FFT Operator

The transformer model is known to be computationally demanding, and proh...

0 Ziwei He, et al. ∙

research

∙ 04/10/2023

Asymmetric Polynomial Loss For Multi-Label Classification

Various tasks are reformulated as multi-label classification problems, i...

0 Yusheng Huang, et al. ∙

research

∙ 02/24/2023

Few-Shot Table-to-Text Generation with Prompt-based Adapter

Pre-trained language models (PLMs) have made remarkable progress in tabl...

0 Zhixin Guo, et al. ∙

research

∙ 02/19/2023

Text Classification in the Wild: a Large-scale Long-tailed Name Normalization Dataset

Real-world data usually exhibits a long-tailed distribution,with a few f...

0 Jiexing Qi, et al. ∙

research

∙ 02/09/2023

Few-Shot Table-to-Text Generation with Prompt Planning and Knowledge Memorization

Pre-trained language models (PLM) have achieved remarkable advancement i...

0 Zhixin Guo, et al. ∙

research

∙ 02/03/2023

Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing

Most graph neural networks follow the message passing mechanism. However...

0 Yunchong Song, et al. ∙

research

∙ 10/21/2022

Text Editing as Imitation Game

Text editing, such as grammatical error correction, arises naturally fro...

7 Ning Shi, et al. ∙

research

∙ 10/21/2022

Syntax-guided Localized Self-attention by Constituency Syntactic Distance

Recent works have revealed that Transformers are implicitly learning the...

1 Shengyuan Hou, et al. ∙

research

∙ 09/22/2022

INFINITY: A Simple Yet Effective Unsupervised Framework for Graph-Text Mutual Conversion

Graph-to-text (G2T) generation and text-to-graph (T2G) triple extraction...

0 Yi Xu, et al. ∙

research

∙ 05/15/2022

Transkimmer: Transformer Learns to Layer-wise Skim

Transformer architecture has become the de-facto model for many machine ...

7 Yue Guan, et al. ∙

research

∙ 05/14/2022

RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL

Relational structures such as schema linking and schema encoding have be...

0 Jiexing Qi, et al. ∙

research

∙ 02/24/2022

Leveraging Unimodal Self-Supervised Learning for Multimodal Audio-Visual Speech Recognition

Training Transformer-based models demands a large amount of data, while ...

0 Xichen Pan, et al. ∙

research

∙ 12/16/2021

Block-Skim: Efficient Question Answering for Transformer

Transformer models have achieved promising results on natural language p...

5 Yue Guan, et al. ∙

research

∙ 06/12/2021

Incorporating External POS Tagger for Punctuation Restoration

Punctuation restoration is an important post-processing step in automati...

0 Ning Shi, et al. ∙

research

∙ 05/29/2021

Annotation Inconsistency and Entity Bias in MultiWOZ

MultiWOZ is one of the most popular multi-domain task-oriented dialog da...

0 Kun Qian, et al. ∙

research

∙ 12/05/2020

Reciprocal Supervised Learning Improves Neural Machine Translation

Despite the recent success on image classification, self-training has on...

0 Minkai Xu, et al. ∙

research

∙ 05/12/2020

Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance Approach

It is commonly believed that knowledge of syntactic structure should imp...

0 Wenyu Du, et al. ∙

research

∙ 10/29/2019

Ordered Memory

Stack-augmented recurrent neural networks (RNNs) have been of interest t...

0 Yikang Shen, et al. ∙

research

∙ 08/28/2019

Interactive Language Learning by Question Answering

Humans observe and interact with the world to acquire knowledge. However...

0 Xingdi Yuan, et al. ∙

research

∙ 06/12/2018

Focused Hierarchical RNNs for Conditional Sequence Processing

Recurrent Neural Networks (RNNs) with attention mechanisms have obtained...

0 Nan Rosemary Ke, et al. ∙

research

∙ 06/11/2018

Straight to the Tree: Constituency Parsing with Neural Syntactic Distance

In this work, we propose a novel constituency parsing scheme. The model ...

2 Yikang Shen, et al. ∙

research

∙ 01/20/2018

A Deep Reinforcement Learning Chatbot (Short Version)

We present MILABOT: a deep reinforcement learning chatbot developed by t...

0 Iulian V. Serban, et al. ∙

research

∙ 11/02/2017

Neural Language Modeling by Jointly Learning Syntax and Lexicon

We propose a neural language model capable of unsupervised syntactic str...

0 Yikang Shen, et al. ∙

research

∙ 09/07/2017

A Deep Reinforcement Learning Chatbot

We present MILABOT: a deep reinforcement learning chatbot developed by t...

0 Iulian V. Serban, et al. ∙

research

∙ 03/09/2017

A Structured Self-attentive Sentence Embedding

This paper proposes a new model for extracting an interpretable sentence...

0 Zhouhan Lin, et al. ∙

research

∙ 08/24/2016

Recurrent Neural Networks With Limited Numerical Precision

Recurrent Neural Networks (RNNs) produce state-of-art performance on man...

0 Joachim Ott, et al. ∙

research

∙ 05/09/2016

Theano: A Python framework for fast computation of mathematical expressions

Theano is a Python library that allows to define, optimize, and evaluate...

0 The Theano Development Team, et al. ∙

research

∙ 02/26/2016

Architectural Complexity Measures of Recurrent Neural Networks

In this paper, we systematically analyze the connecting architectures of...

0 Saizheng Zhang, et al. ∙

research

∙ 11/09/2015

Spectral-Spatial Classification of Hyperspectral Image Using Autoencoders

Hyperspectral image (HSI) classification is a hot topic in the remote se...

0 Zhouhan Lin, et al. ∙

research

∙ 11/09/2015

How far can we go without convolution: Improving fully-connected networks

We propose ways to improve the performance of fully connected networks. ...

0 Zhouhan Lin, et al. ∙

research

∙ 10/11/2015

Neural Networks with Few Multiplications

For most deep learning algorithms training is notoriously time consuming...

0 Zhouhan Lin, et al. ∙

Zhouhan Lin

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