Papers with Code 아카이브
Text Generation
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Text Generation is the task of generating text with the goal of appearing indistinguishable to human-written text. This task is more formally known as "natural language generation" in the literature.
Text generation can be addressed with Markov processes or deep generative models like LSTMs. Recently, some of the most advanced methods for text generation include BART, GPT and other GAN-based approaches. Text generation systems are evaluated either through human ratings or automatic evaluation metrics like METEOR, ROUGE, and BLEU.
Further readings:
<span style="color:grey; opacity: 0.6">( Image credit: Adversarial Ranking for Language Generation )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/davisking/dlib-models
https://github.com/dawn0815/UniSA
https://github.com/dccuchile/CC6204
https://github.com/debjitpaul/refiner
https://github.com/declare-lab/conv-emotion
https://github.com/deepmind/haiku
https://github.com/deepmipt/bert/tree/feat/multi_gpu
https://github.com/deepsense-ai/unblackboxing_webinar
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/deepset-ai/haystack
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
https://github.com/demegire/Parameterization-of-Hypercomplex-Multiplications
https://github.com/demelin/nematode
https://github.com/denisewong1/ASX300
Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs
https://github.com/derylucio/Transformer
https://github.com/desire2020/RankGAN
SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
https://github.com/devJWSong/bert-crf-entity-recognition-pytorch
ReCoSa: Detecting the Relevant Contexts with Self-Attention for Multi-turn Dialogue Generation
https://github.com/devJWSong/gpt2-chatbot-pytorch
Personalizing Dialogue Agents: I have a dog, do you have pets too?
https://github.com/devhemza/BERTweet_sentiment_analysis
HuggingFace's Transformers: State-of-the-art Natural Language Processing
https://github.com/devjwsong/gpt2-dialogue-generation-pytorch
Personalizing Dialogue Agents: I have a dog, do you have pets too?
https://github.com/dgonzalez-ri/neural-visual-storyteller
https://github.com/dhansmair/flamingo-mini
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/dhiraa/tener
https://github.com/dice-group/NABU
Graph2Seq: Graph to Sequence Learning with Attention-based Neural Networks
https://github.com/dig-team/hanna-benchmark-asg
CTRL: A Conditional Transformer Language Model for Controllable Generation
https://github.com/dinobby/hypemo
Towards Empathetic Open-domain Conversation Models: a New Benchmark and Dataset
https://github.com/distractor-generation/dg_survey
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/dl-nlp/dl-nlp.github.io
https://github.com/dladustn95/ENMODEL
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/dladustn95/dialogGenerator_transformer
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/dladustn95/enLanguageModel
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
https://github.com/dmlc/dgl/tree/master/examples/pytorch/graphwriter
Text Generation from Knowledge Graphs with Graph Transformers
https://github.com/dmlc/gluon-nlp
https://github.com/dmlls/negate
This is not correct! Negation-aware Evaluation of Language Generation Systems
https://github.com/doc-doc/NExT-OE
https://github.com/docarray/docarray
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
https://github.com/dojoteef/storium-frontend
STORIUM: A Dataset and Evaluation Platform for Machine-in-the-Loop Story Generation
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