https://github.com/thu-coai/cotk
공식 코드CoTK: An Open-Source Toolkit for Fast Development and Fair Evaluation of Text Generation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
CoTK: An Open-Source Toolkit for Fast Development and Fair Evaluation of Text Generation
CTRLEval: An Unsupervised Reference-Free Metric for Evaluating Controlled Text Generation
Directed Acyclic Transformer Pre-training for High-quality Non-autoregressive Text Generation
LOT: A Story-Centric Benchmark for Evaluating Chinese Long Text Understanding and Generation
Tailoring Language Generation Models under Total Variation Distance
StoryWriter: A Multi-Agent Framework for Long Story Generation
An Extensible Plug-and-Play Method for Multi-Aspect Controllable Text Generation
Ouroboros: Generating Longer Drafts Phrase by Phrase for Faster Speculative Decoding
Mind the Style of Text! Adversarial and Backdoor Attacks Based on Text Style Transfer
Identifying Query-Relevant Neurons in Large Language Models for Long-Form Texts
RT-KGD: Relation Transition Aware Knowledge-Grounded Dialogue Generation
TempLM: Distilling Language Models into Template-Based Generators
GLAC Net: GLocal Attention Cascading Networks for Multi-image Cued Story Generation
Factorising Meaning and Form for Intent-Preserving Paraphrasing
Fusing task-oriented and open-domain dialogues in conversational agents
Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models
A Cross-Attention Augmented Model for Event-Triggered Context-Aware Story Generation
Complex Reasoning over Logical Queries on Commonsense Knowledge Graphs
Benchmarking and Improving Compositional Generalization of Multi-aspect Controllable Text Generation
Beyond checkmate: exploring the creative chokepoints in AI text
MacLaSa: Multi-Aspect Controllable Text Generation via Efficient Sampling from Compact Latent Space
RegaVAE: A Retrieval-Augmented Gaussian Mixture Variational Auto-Encoder for Language Modeling
CR-Walker: Tree-Structured Graph Reasoning and Dialog Acts for Conversational Recommendation
Exploring Automatic Text Simplification of German Narrative Documents
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.