โโOptimus: Organizing Sentences via Pre-trained Modeling of a Latent Space
The authors propose the first large-scale language VAE model โ Optimus.
This new model uses BERT weights in the encoder and GPT-2 weights in the decoder. Thanks to this Optimus supports NLU and text generation tasks. Learned language representation is more universal, which means that it is easier to fine-tune this model to a new domain/task. Also, Optimus can control high-level semantics in text generation (tense, topic, sentiment).
There are several novel contributions, which are made thanks to this work:
โ latent vector injection: two schemes are suggested to inject conditioning vectors into GPT-2 without retraining it;
โ the idea to combine BERT and GPT-2 could inspire people to integrate existing language models into larger and ever more complex models;
โ pre-training on a big corpora is an effective approach to reduce KL vanishing;
โ VAE is a good approach to balance the compactness and usability of learned representations;
โ pre-training latent space improves performance on several language tasks;
Experimental results on a wide range of tasks and datasets have demonstrated the strong performance of OPTIMUS, including new state-of-the-art for language VAEs.
Paper: https://arxiv.org/abs/2004.04092v1
Github: https://github.com/ChunyuanLI/Optimus
#deeplearning #nlp #nlu #transformer #vae #bert #gpt2
The authors propose the first large-scale language VAE model โ Optimus.
This new model uses BERT weights in the encoder and GPT-2 weights in the decoder. Thanks to this Optimus supports NLU and text generation tasks. Learned language representation is more universal, which means that it is easier to fine-tune this model to a new domain/task. Also, Optimus can control high-level semantics in text generation (tense, topic, sentiment).
There are several novel contributions, which are made thanks to this work:
โ latent vector injection: two schemes are suggested to inject conditioning vectors into GPT-2 without retraining it;
โ the idea to combine BERT and GPT-2 could inspire people to integrate existing language models into larger and ever more complex models;
โ pre-training on a big corpora is an effective approach to reduce KL vanishing;
โ VAE is a good approach to balance the compactness and usability of learned representations;
โ pre-training latent space improves performance on several language tasks;
Experimental results on a wide range of tasks and datasets have demonstrated the strong performance of OPTIMUS, including new state-of-the-art for language VAEs.
Paper: https://arxiv.org/abs/2004.04092v1
Github: https://github.com/ChunyuanLI/Optimus
#deeplearning #nlp #nlu #transformer #vae #bert #gpt2
โโ๐๐ถImproved audio generative model from OpenAI
Wow! OpenAI just released Jukebox โ neural net and service that generates music from genre, artist name, and some lyrics that you can supply. It is can generate even some singing like from corrupted magnet compact cassette.
Some of the sounds seem it is from hell. Agonizing Michel Jakson for example or Creepy Eminiem or Celien Dion
#OpenAI 's approach is to use 3 levels of quantized variational autoencoders VQVAE-2 to learn discrete representations of audio and compress audio by 8x, 32x, and 128x and use the spectral loss to reconstruct spectrograms. And after that, they use sparse transformers conditioned on lyrics to generate new patterns and upsample it to higher discrete samples and decode it to the song.
The net can even learn and generates some solo parts during the track.
explore some creepy songs: https://jukebox.openai.com/
code: https://github.com/openai/jukebox/
paper: https://cdn.openai.com/papers/jukebox.pdf
blog: https://openai.com/blog/jukebox/
#openAI #music #sound #cool #fan #creepy #vae #audiolearning #soundlearning
Wow! OpenAI just released Jukebox โ neural net and service that generates music from genre, artist name, and some lyrics that you can supply. It is can generate even some singing like from corrupted magnet compact cassette.
Some of the sounds seem it is from hell. Agonizing Michel Jakson for example or Creepy Eminiem or Celien Dion
#OpenAI 's approach is to use 3 levels of quantized variational autoencoders VQVAE-2 to learn discrete representations of audio and compress audio by 8x, 32x, and 128x and use the spectral loss to reconstruct spectrograms. And after that, they use sparse transformers conditioned on lyrics to generate new patterns and upsample it to higher discrete samples and decode it to the song.
The net can even learn and generates some solo parts during the track.
explore some creepy songs: https://jukebox.openai.com/
code: https://github.com/openai/jukebox/
paper: https://cdn.openai.com/papers/jukebox.pdf
blog: https://openai.com/blog/jukebox/
#openAI #music #sound #cool #fan #creepy #vae #audiolearning #soundlearning
๐ฆ Hi!
We are the first Telegram Data Science channel.
Channel was started as a collection of notable papers, news and releases shared for the members of Open Data Science (ODS) community. Through the years of just keeping the thing going we grew to an independent online Media supporting principles of Free and Open access to the information related to Data Science.
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We are the first Telegram Data Science channel.
Channel was started as a collection of notable papers, news and releases shared for the members of Open Data Science (ODS) community. Through the years of just keeping the thing going we grew to an independent online Media supporting principles of Free and Open access to the information related to Data Science.
Ultimate Posts
* Where to start learning more about Data Science. https://github.com/open-data-science/ultimate_posts/tree/master/where_to_start
* @opendatascience channel audience research. https://github.com/open-data-science/ods_channel_stats_eda
Open Data Science
ODS.ai is an international community of people anyhow related to Data Science.
Website: https://ods.ai
Hashtags
Through the years we accumulated a big collection of materials, most of them accompanied by hashtags.
#deeplearning #DL โ post about deep neural networks (> 1 layer)
#cv โ posts related to Computer Vision. Pictures and videos
#nlp #nlu โ Natural Language Processing and Natural Language Understanding. Texts and sequences
#audiolearning #speechrecognition โ related to audio information processing
#ar โ augmeneted reality related content
#rl โ Reinforcement Learning (agents, bots and neural networks capable of playing games)
#gan #generation #generatinveart #neuralart โ about neural artt and image generation
#transformer #vqgan #vae #bert #clip #StyleGAN2 #Unet #resnet #keras #Pytorch #GPT3 #GPT2 โ related to special architectures or frameworks
#coding #CS โ content related to software engineering sphere
#OpenAI #microsoft #Github #DeepMind #Yandex #Google #Facebook #huggingface โ hashtags related to certain companies
#productionml #sota #recommendation #embeddings #selfdriving #dataset #opensource #analytics #statistics #attention #machine #translation #visualization
Chats
- Data Science Chat https://t.me/datascience_chat
- ODS Slack through invite form at website
ODS resources
* Main website: https://ods.ai
* ODS Community Telegram Channel (in Russian): @ods_ru
* ML trainings Telegram Channel: @mltrainings
* ODS Community Twitter: https://twitter.com/ods_ai
Feedback and Contacts
You are welcome to reach administration through telegram bot: @opendatasciencebot
GitHub
ultimate_posts/where_to_start at master ยท open-data-science/ultimate_posts
Ultimate posts for opendatascience telegram channel - open-data-science/ultimate_posts