ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2301.09237
  4. Cited By
Semantic-aware Contrastive Learning for Electroencephalography-to-Text
  Generation with Curriculum Learning

Semantic-aware Contrastive Learning for Electroencephalography-to-Text Generation with Curriculum Learning

23 January 2023
Xiachong Feng
Xiaocheng Feng
Bing Qin
ArXivPDFHTML

Papers citing "Semantic-aware Contrastive Learning for Electroencephalography-to-Text Generation with Curriculum Learning"

14 / 14 papers shown
Title
Toward a realistic model of speech processing in the brain with
  self-supervised learning
Toward a realistic model of speech processing in the brain with self-supervised learning
Juliette Millet
Charlotte Caucheteux
Pierre Orhan
Yves Boubenec
Alexandre Gramfort
Ewan Dunbar
Christophe Pallier
J. King
74
97
0
03 Jun 2022
Inter-subject Contrastive Learning for Subject Adaptive EEG-based Visual
  Recognition
Inter-subject Contrastive Learning for Subject Adaptive EEG-based Visual Recognition
Pilhyeon Lee
Sunhee Hwang
Jewook Lee
Minjung Shin
Seogkyu Jeon
H. Byun
46
11
0
07 Feb 2022
Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot
  Sentiment Classification
Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification
Zhenhailong Wang
Heng Ji
120
78
0
05 Dec 2021
Contrastive Learning of Subject-Invariant EEG Representations for
  Cross-Subject Emotion Recognition
Contrastive Learning of Subject-Invariant EEG Representations for Cross-Subject Emotion Recognition
Xinke Shen
Xianggen Liu
Xin Hu
Dan Zhang
Sen Song
45
149
0
20 Sep 2021
SimCSE: Simple Contrastive Learning of Sentence Embeddings
SimCSE: Simple Contrastive Learning of Sentence Embeddings
Tianyu Gao
Xingcheng Yao
Danqi Chen
AILaw
SSL
261
3,396
0
18 Apr 2021
Subject-Aware Contrastive Learning for Biosignals
Subject-Aware Contrastive Learning for Biosignals
Joseph Y. Cheng
Hanlin Goh
Kaan Dogrusoz
Oncel Tuzel
Erdrin Azemi
SSL
50
112
0
30 Jun 2020
DeCLUTR: Deep Contrastive Learning for Unsupervised Textual
  Representations
DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations
John Giorgi
Osvald Nitski
Bo Wang
Gary D. Bader
SSL
93
497
0
05 Jun 2020
Conformer: Convolution-augmented Transformer for Speech Recognition
Conformer: Convolution-augmented Transformer for Speech Recognition
Anmol Gulati
James Qin
Chung-Cheng Chiu
Niki Parmar
Yu Zhang
...
Wei Han
Shibo Wang
Zhengdong Zhang
Yonghui Wu
Ruoming Pang
223
3,139
0
16 May 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
369
18,778
0
13 Feb 2020
PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive
  Summarization
PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
Jingqing Zhang
Yao-Min Zhao
Mohammad Saleh
Peter J. Liu
RALM
3DGS
278
2,049
0
18 Dec 2019
ZuCo 2.0: A Dataset of Physiological Recordings During Natural Reading
  and Annotation
ZuCo 2.0: A Dataset of Physiological Recordings During Natural Reading and Annotation
Nora Hollenstein
M. Troendle
Ce Zhang
N. Langer
70
89
0
02 Dec 2019
Momentum Contrast for Unsupervised Visual Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
199
12,085
0
13 Nov 2019
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language
  Generation, Translation, and Comprehension
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
M. Lewis
Yinhan Liu
Naman Goyal
Marjan Ghazvininejad
Abdel-rahman Mohamed
Omer Levy
Veselin Stoyanov
Luke Zettlemoyer
AIMat
VLM
249
10,829
0
29 Oct 2019
Exploring the Limits of Transfer Learning with a Unified Text-to-Text
  Transformer
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel
Noam M. Shazeer
Adam Roberts
Katherine Lee
Sharan Narang
Michael Matena
Yanqi Zhou
Wei Li
Peter J. Liu
AIMat
427
20,181
0
23 Oct 2019
1