All Projects → tony-hong → event-embedding-multitask

tony-hong / event-embedding-multitask

Licence: GPL-3.0 license
*SEM 2018: Learning Distributed Event Representations with a Multi-Task Approach

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to event-embedding-multitask

Simple-Sentence-Similarity
Exploring the simple sentence similarity measurements using word embeddings
Stars: ✭ 99 (+350%)
Mutual labels:  sentence-similarity, sentence-embeddings
AnnA Anki neuronal Appendix
Using machine learning on your anki collection to enhance the scheduling via semantic clustering and semantic similarity
Stars: ✭ 39 (+77.27%)
Mutual labels:  embedding, sentence-embeddings
TaskRouting
(ICCV 2019 Oral) Many Task Learning With Task Routing http://openaccess.thecvf.com/content_ICCV_2019/html/Strezoski_Many_Task_Learning_With_Task_Routing_ICCV_2019_paper.html
Stars: ✭ 61 (+177.27%)
Mutual labels:  multitask, multitask-learning
Chinese Word Vectors
100+ Chinese Word Vectors 上百种预训练中文词向量
Stars: ✭ 9,548 (+43300%)
Mutual labels:  embeddings, embedding
watset-java
An implementation of the Watset clustering algorithm in Java.
Stars: ✭ 24 (+9.09%)
Mutual labels:  semantics, embeddings
lambda-notebook
Lambda Notebook: Formal Semantics in Jupyter
Stars: ✭ 16 (-27.27%)
Mutual labels:  semantics, linguistics
muse-as-service
REST API for sentence tokenization and embedding using Multilingual Universal Sentence Encoder.
Stars: ✭ 45 (+104.55%)
Mutual labels:  embeddings, sentence-embeddings
unify-srl
Unifying Cross-Lingual Semantic Role Labeling with Heterogeneous Linguistic Resources (NAACL-2021).
Stars: ✭ 12 (-45.45%)
Mutual labels:  semantics, semantic-role-labeling
pfootprint
Political Discourse Analysis Using Pre-Trained Word Vectors.
Stars: ✭ 20 (-9.09%)
Mutual labels:  semantics, linguistics
geometric embedding
"Zero-Training Sentence Embedding via Orthogonal Basis" paper implementation
Stars: ✭ 19 (-13.64%)
Mutual labels:  embeddings
keras-pos-embd
Position embedding layers in Keras
Stars: ✭ 61 (+177.27%)
Mutual labels:  embedding
poesy
Poetic processing, for Python.
Stars: ✭ 28 (+27.27%)
Mutual labels:  linguistics
siamese dssm
siamese dssm sentence_similarity sentece_similarity_rank tensorflow
Stars: ✭ 59 (+168.18%)
Mutual labels:  sentence-similarity
nyt-first-said
Tweets when words are published for the first time in the NYT
Stars: ✭ 222 (+909.09%)
Mutual labels:  linguistics
ChineseNER
中文NER的那些事儿
Stars: ✭ 241 (+995.45%)
Mutual labels:  multitask-learning
embedding study
中文预训练模型生成字向量学习,测试BERT,ELMO的中文效果
Stars: ✭ 94 (+327.27%)
Mutual labels:  embeddings
score-zeroshot
Semantically consistent regularizer for zero-shot learning
Stars: ✭ 65 (+195.45%)
Mutual labels:  semantics
word-embeddings-from-scratch
Creating word embeddings from scratch and visualize them on TensorBoard. Using trained embeddings in Keras.
Stars: ✭ 22 (+0%)
Mutual labels:  embeddings
koika
A core language for rule-based hardware design 🦑
Stars: ✭ 103 (+368.18%)
Mutual labels:  semantics
DREML
PyTorch implementation of Deep Randomized Ensembles for Metric Learning(ECCV2018)
Stars: ✭ 67 (+204.55%)
Mutual labels:  embedding

Event Embeddings with a Multi-Task Approach

This is the repository for the *SEM 2018 paper "Learning Distributed Event Representations with a Multi-Task Approach" by Xudong Hong, Asad Sayeed and Vera Demberg.

The published paper is star-sem-paper.pdf and the supplemental document is star-sem-supplemental.pdf. The source code and more information are in event-embedding.

If you use our code in your work, please cite our paper:

@inproceedings{hong2018learning,
    title={Learning distributed event representations with a multi-task approach},
    author={Hong, Xudong and Sayeed, Asad and Demberg, Vera},
    booktitle={Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics},
    pages={11--21},
    year={2018}
}

Contact

Feel free to contact Xudong Hong if you have any question!

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].