https://github.com/PaddlePaddle/PaddleNLP/tree/develop/model_zoo/plato-xl
PLATO-XL: Exploring the Large-scale Pre-training of Dialogue Generation
Papers with Code 아카이브
Text Generation
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- 평가표
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- 보존된 평가 기록
- 54
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/PaddlePaddle/PaddleNLP/tree/develop/paddlenlp/transformers/ctrl
CTRL: A Conditional Transformer Language Model for Controllable Generation
https://github.com/PaddlePaddle/PaddleNLP/tree/develop/pipelines/examples/text_to_image
ERNIE-ViLG: Unified Generative Pre-training for Bidirectional Vision-Language Generation
https://github.com/PaddlePaddle/PaddleSpeech
https://github.com/Parth27/Data2Text
Table-to-text Generation by Structure-aware Seq2seq Learning
https://github.com/Pendulibrium/ai-visual-storytelling-seq2seq
Effective Approaches to Attention-based Neural Machine Translation
https://github.com/Peyvand-Andalibi/NL2Code
A Syntactic Neural Model for General-Purpose Code Generation
https://github.com/Pezhin/best_yelp_review_project_ever
https://github.com/Pillercottrer/radcap_project
https://github.com/Pranav-Patil-7/Automatic_Image_Captioning_Project
https://github.com/PrideLee/sentiment-analysis
https://github.com/QwenLM/Qwen2.5-Omni
https://github.com/RUCAIBox/KGSF
Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion
https://github.com/RUCAIBox/Slow_Thinking_with_LLMs
Think More, Hallucinate Less: Mitigating Hallucinations via Dual Process of Fast and Slow Thinking
https://github.com/Rami97rgb/French-to-English-Translator
https://github.com/Rcrossmeister/Knowledge-to-SQL
LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
https://github.com/Rcrossmeister/RLQG
LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
https://github.com/ReleasedBrainiac/GraphToSequenceNN
Graph2Seq: Graph to Sequence Learning with Attention-based Neural Networks
https://github.com/RemiArbache/style-transfer-M2
https://github.com/Remiphilius/PoemesProfonds
https://github.com/RenXiangyuan/tf_bert
https://github.com/RoT-llm/Reversal-of-Thought
https://github.com/Rudedaisy/attention-is-all-you-need-pytorch
https://github.com/S-Abdelnabi/awt
Adversarial Watermarking Transformer: Towards Tracing Text Provenance with Data Hiding
https://github.com/SCismycat/bert_code_view
https://github.com/SYangDong/bert-with-frozen-code
https://github.com/SagesAi/terminal-agent
Automatic Unit Test Data Generation and Actor-Critic Reinforcement Learning for Code Synthesis
https://github.com/SamuelCahyawijaya/indobenchmark-toolkit
IndoNLG: Benchmark and Resources for Evaluating Indonesian Natural Language Generation
https://github.com/SamuelNguyen1998/Vietnamese_Handwriting_Recognition
https://github.com/Satan012/BERT
https://github.com/SathwikTejaswi/Neural-Image-Captioning
https://github.com/ScientiaEtVeritas/NeuralMachineTranslation
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/SeoroMin/transformer_pytorch
https://github.com/SeoroMin/transformer_pytorch_ver2
https://github.com/SforAiDl/CountCLIP
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/Sharpiless/Versailles-text-generation-with-paddlepaddle
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.