https://github.com/LC1332/Chat-Haruhi-Suzumiya
공식 코드ChatHaruhi: Reviving Anime Character in Reality via Large Language Model
Papers with Code 아카이브
Text Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 25
- 평가표
- 155
- 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/LCS2-IIITD/Hate_Norm
공식 코드Proactively Reducing the Hate Intensity of Online Posts via Hate Speech Normalization
https://github.com/LCS2-IIITD/LUMEN-Explaining-Memes
공식 코드What do you MEME? Generating Explanations for Visual Semantic Role Labelling in Memes
https://github.com/LCS2-IIITD/summarization_bias
공식 코드Corpora Evaluation and System Bias Detection in Multi-document Summarization
https://github.com/LUMIA-Group/SH2
공식 코드SH2: Self-Highlighted Hesitation Helps You Decode More Truthfully
https://github.com/Lancelot39/KGSF
공식 코드Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion
https://github.com/LantaoYu/SeqGAN
공식 코드SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
https://github.com/Ledengary/PGST
공식 코드https://github.com/LeoLaugier/conditional-auto-encoder-text-to-text-transfer-transformer
공식 코드Civil Rephrases Of Toxic Texts With Self-Supervised Transformers
https://github.com/Lingzhi-WANG/Datasets-for-Quotation-Recommendation
공식 코드Continuity of Topic, Interaction, and Query: Learning to Quote in Online Conversations
https://github.com/Lireanstar/BPDG
공식 코드Bilateral Personalized Dialogue Generation with Contrastive Learning
https://github.com/LiyingCheng95/EntityDescriptionGeneration
공식 코드ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
https://github.com/LuJunru/CHIME
공식 코드CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering
https://github.com/Luffy03/UniBiomed
공식 코드UniBiomed: A Universal Foundation Model for Grounded Biomedical Image Interpretation
https://github.com/LuoweiZhou/VLP
공식 코드Unified Vision-Language Pre-Training for Image Captioning and VQA
https://github.com/M0RJIQUE/tencdm
공식 코드TEncDM: Understanding the Properties of the Diffusion Model in the Space of Language Model Encodings
https://github.com/MIMIFY/SS-Bench
공식 코드SS-GEN: A Social Story Generation Framework with Large Language Models
https://github.com/Machine-Learning-Tokyo/Poetry-GAN
공식 코드https://github.com/Maluuba/nlg-eval
공식 코드https://github.com/MattAlexMiracle/SmartPatch
공식 코드SmartPatch: Improving Handwritten Word Imitation with Patch Discriminators
https://github.com/Max-Fu/tvl
공식 코드A Touch, Vision, and Language Dataset for Multimodal Alignment
https://github.com/McGill-DMaS/Authorship-Anonymization
공식 코드ER-AE: Differentially Private Text Generation for Authorship Anonymization
https://github.com/McGill-DMaS/AuthorshipAnonymization
공식 코드ER-AE: Differentially Private Text Generation for Authorship Anonymization
https://github.com/McGill-NLP/statcan-dialogue-dataset
공식 코드The StatCan Dialogue Dataset: Retrieving Data Tables through Conversations with Genuine Intents
https://github.com/McGill-NLP/weblinx
공식 코드WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
https://github.com/McGill-NLP/webllama
공식 코드WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
https://github.com/Milozms/TSMH
공식 코드https://github.com/MinkyuKim26/Prefix_AAC_ICASSP2023
공식 코드https://github.com/MiriUll/negation_aware_evaluation
공식 코드This is not correct! Negation-aware Evaluation of Language Generation Systems
https://github.com/MirunaClinciu/ExBAN
공식 코드A Study of Automatic Metrics for the Evaluation of Natural Language Explanations
https://github.com/MiuLab/DuaLUG
공식 코드Dual Supervised Learning for Natural Language Understanding and Generation
https://github.com/MiuLab/HNLG
공식 코드Natural Language Generation by Hierarchical Decoding with Linguistic Patterns
https://github.com/MiuLab/TaylorGAN
공식 코드TaylorGAN: Neighbor-Augmented Policy Update for Sample-Efficient Natural Language Generation
https://github.com/MonoFormer/MonoFormer
공식 코드MonoFormer: One Transformer for Both Diffusion and Autoregression
https://github.com/MovingKyu/RACoLN
공식 코드https://github.com/NVIDIA/Megatron-LM
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.