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/xhan77/ssd-lm
공식 코드https://github.com/xiangli1999/contrastivedecoding
공식 코드Contrastive Decoding: Open-ended Text Generation as Optimization
https://github.com/xiangli1999/diffusion-lm
공식 코드https://github.com/xiangyu-mm/unifashion
공식 코드UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and Generation
https://github.com/xiangyu-peng/cast_public
공식 코드Inferring the Reader: Guiding Automated Story Generation with Commonsense Reasoning
https://github.com/xiaofei05/tsst
공식 코드https://github.com/xiatingyu/probdiff
공식 코드Language Models can Evaluate Themselves via Probability Discrepancy
https://github.com/xiaweijie1996/full-convolutional-time-series-flow
공식 코드https://github.com/xie-lab-ml/Meissonic-Inference
공식 코드Bag of Design Choices for Inference of High-Resolution Masked Generative Transformer
https://github.com/xiexing0916/ARRA
공식 코드https://github.com/xingwei-warwick/set-aligning-event-temporal-graph-generation
공식 코드Set-Aligning Framework for Auto-Regressive Event Temporal Graph Generation
https://github.com/xinlinpeng/aig-asap
공식 코드Hidding the Ghostwriters: An Adversarial Evaluation of AI-Generated Student Essay Detection
https://github.com/xinnuoxu/miranews
공식 코드MiRANews: Dataset and Benchmarks for Multi-Resource-Assisted News Summarization
https://github.com/xinykou/FGDILP
공식 코드Fine-Grained Detoxification via Instance-Level Prefixes for Large Language Models
https://github.com/xiongsiheng/tg-llm
공식 코드https://github.com/xlhex/extract_and_transfer
공식 코드Model Extraction and Adversarial Transferability, Your BERT is Vulnerable!
https://github.com/xlhex/nlg_api_watermark
공식 코드Protecting Intellectual Property of Language Generation APIs with Lexical Watermark
https://github.com/xmshi-trio/MidMed
공식 코드MidMed: Towards Mixed-Type Dialogues for Medical Consultation
https://github.com/xssstory/SeqCo
공식 코드https://github.com/xsysigma/tencentllmeval
공식 코드TencentLLMEval: A Hierarchical Evaluation of Real-World Capabilities for Human-Aligned LLMs
https://github.com/xt-cyh/codi-eval
공식 코드Benchmarking Large Language Models on Controllable Generation under Diversified Instructions
https://github.com/xu-shitong/diffusion-image-captioning
공식 코드CLIP-Diffusion-LM: Apply Diffusion Model on Image Captioning
https://github.com/xu1998hz/llm_self_bias
공식 코드Pride and Prejudice: LLM Amplifies Self-Bias in Self-Refinement
https://github.com/xu1998hz/sescore
공식 코드Not All Errors are Equal: Learning Text Generation Metrics using Stratified Error Synthesis
https://github.com/xu1998hz/sescore2
공식 코드SESCORE2: Learning Text Generation Evaluation via Synthesizing Realistic Mistakes
https://github.com/xu1998hz/sescore3
공식 코드INSTRUCTSCORE: Explainable Text Generation Evaluation with Finegrained Feedback
https://github.com/xu1998hz/ssl_kba_expert_layman_style_transfer
공식 코드Self-Supervised Knowledge Assimilation for Expert-Layman Text Style Transfer
https://github.com/xuandongzhao/crt
공식 코드https://github.com/xuandongzhao/ginseq
공식 코드Protecting Language Generation Models via Invisible Watermarking
https://github.com/xuandongzhao/ginsew
공식 코드Protecting Language Generation Models via Invisible Watermarking
https://github.com/xuchennlp/s2t
공식 코드Revisiting Interpolation Augmentation for Speech-to-Text Generation
https://github.com/xuekai-zhu/storytrans_public
공식 코드https://github.com/xunannancy/lookbackdecoding
공식 코드https://github.com/xuqiongkai/ALTER
공식 코드ALTER: Auxiliary Text Rewriting Tool for Natural Language Generation
https://github.com/xuzhao0/length-bias-factuality
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.