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Text Generation

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:

( Image credit: Adversarial Ranking for Language Generation )

Papers

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Showing 3151–3200 of 5335 papers

TitleStatusHype
Unifying Large Language Models and Knowledge Graphs: A Roadmap—0
Unifying Structured Data as Graph for Data-to-Text Pre-Training—0
UniGenX: Unified Generation of Sequence and Structure with Autoregressive Diffusion—0
UniMS: A Unified Framework for Multimodal Summarization with Knowledge Distillation—0
Universal Multimodal Representation for Language Understanding—0
Universal Self-Adaptive Prompting—0
Universal Visuo-Tactile Video Understanding for Embodied Interaction—0
Unleashing the Power of LLMs in Dense Retrieval with Query Likelihood Modeling—0
Unlocking Memorization in Large Language Models with Dynamic Soft Prompting—0
Unmasking Nationality Bias: A Study of Human Perception of Nationalities in AI-Generated Articles—0
Unraveling Text Generation in LLMs: A Stochastic Differential Equation Approach—0
Unseen Entity Handling in Complex Question Answering over Knowledge Base via Language Generation—0
Unsupervised and Distributional Detection of Machine-Generated Text—0
Unsupervised Concept-to-text Generation with Hypergraphs—0
Unsupervised Content Discovery from Concise Summaries—0
Unsupervised Discovery of Interpretable Latent Manipulations in Language VAEs—0
Unsupervised KB-to-Text Generation with Auxiliary Triple Extraction using Dual Learning—0
Unsupervised Melody-Guided Lyrics Generation—0
Unsupervised Morphology-Based Vocabulary Expansion—0
Unsupervised Multi-View Post-OCR Error Correction With Language Models—0
Unsupervised Neural Stylistic Text Generation using Transfer learning and Adapters—0
Unsupervised Pidgin Text Generation By Pivoting English Data and Self-Training—0
Unsupervised Prediction of Acceptability Judgements—0
Unsupervised Pre-training for Natural Language Generation: A Literature Review—0
Unsupervised Random Walk Sentence Embeddings: A Strong but Simple Baseline—0
Unsupervised Sentence Enhancement for Automatic Summarization—0
Unsupervised structured semantic inference for spoken dialog reservation tasks—0
Unsupervised Text Generation by Learning from Search—0
Unsupervised Token-wise Alignment to Improve Interpretation of Encoder-Decoder Models—0
Unveiling LLM Evaluation Focused on Metrics: Challenges and Solutions—0
Unveiling the potential of large language models in generating semantic and cross-language clones—0
Up-cycling Data for Natural Language Generation—0
Urban Mobility Assessment Using LLMs—0
Urdu & Hindi Poetry Generation using Neural Networks—0
User-Controlled, Robust Natural Language Generation from an Evolving Knowledge Base—0
Using a Graph-based Coherence Model in Document-Level Machine Translation—0
Using a Keyness Metric for Single and Multi Document Summarisation—0
Using BERT Encoding and Sentence-Level Language Model for Sentence Ordering—0
Using Conceptual Spaces to Model Domain Knowledge in Data-to-Text Systems—0
Using Discourse Information for Paraphrase Extraction—0
Using Electronic Dictionaries and NooJ to Generate Sentences Containing English Phrasal Verbs—0
Using GAN-based models to sentimental analysis on imbalanced datasets in education domain—0
Using Gaze to Predict Text Readability—0
Using graph transformation algorithms to generate natural language equivalents of icons expressing medical concepts—0
Using Integer Linear Programming for Content Selection, Lexicalization, and Aggregation to Produce Compact Texts from OWL Ontologies—0
Using Integer Linear Programming in Concept-to-Text Generation to Produce More Compact Texts—0
Using Integrated Gradients and Constituency Parse Trees to explain Linguistic Acceptability learnt by BERT—0
Using Language Groundings for Context-Sensitive Text Prediction—0
EAT: a simple and versatile semantic representation format for multi-purpose NLP—0
Using NLG for speech synthesis of mathematical sentences—0
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All datasetsDARTCOCO CaptionsEMNLP2017 WMTReDialCommonGenROCStoriesChinese PoemsCzech restaurant informationOpenWebTextSciQYahoo QuestionsADGEN

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1T5B BaselineBLEU48.74—Unverified
2FactT5BBLEU48.37—Unverified
3JointGT BaselineBLEU47.51—Unverified
4FactJointGTBLEU47.39—Unverified
5Control Prefixes (T5-large)METEOR0.41—Unverified
6T5METEOR0.12—Unverified
7BARTMETEOR0.11—Unverified
#ModelMetricClaimedVerifiedStatus
1LeakGANBLEU-20.95—Unverified
2partGANBLEU-20.91—Unverified
3RankGANBLEU-20.85—Unverified
4RelGAN (100)BLEU-20.85—Unverified
5SeqGANBLEU-20.83—Unverified
#ModelMetricClaimedVerifiedStatus
1LeakGANBLEU-20.96—Unverified
2PPOGANBLEU-20.91—Unverified
3RelGANBLEU-20.88—Unverified
4SeqGANBLEU-20.86—Unverified
5RankGANBLEU-20.78—Unverified
#ModelMetricClaimedVerifiedStatus
1UniCRSDistinct-30.65—Unverified
2CRFRDistinct-30.52—Unverified
3KGSFDistinct-30.43—Unverified
4C2CRSDistinct-30.33—Unverified
5KBRDDistinct-30.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UniLMCIDEr14.92—Unverified
2BART (TextBox 2.0)CIDEr12.98—Unverified
3BARTMETEOR0.3—Unverified
4T5METEOR0.29—Unverified
#ModelMetricClaimedVerifiedStatus
1Beam search + A*esque (beam)BLEU-134.4—Unverified
2Beam search + A*esque (sample)BLEU-134.4—Unverified
3Beam search + A*esque (greedy)BLEU-134.3—Unverified
4Beam searchBLEU-133.7—Unverified
#ModelMetricClaimedVerifiedStatus
1RankGANBLEU-20.81—Unverified
2SeqGANBLEU-20.74—Unverified
3LeakGANBLEU-20.46—Unverified
#ModelMetricClaimedVerifiedStatus
1TGen++METEOR0.17—Unverified
2TGenMETEOR0.15—Unverified
3TGen+METEOR0.15—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT2-124Meval_loss3.12—Unverified
2GPT2-81M-LOOPeval_loss3.11—Unverified
3GPT2-Hermiteeval_loss2.91—Unverified
#ModelMetricClaimedVerifiedStatus
1LLaMA-65B+CFG (zero-shot)Accuracy96.6—Unverified
2LLaMA-30B+CFG (zero-shot)Accuracy96.4—Unverified
3LLaMA-13B+CFG (zero-shot)Accuracy95.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN-VAENLL332.1—Unverified
2SA-VAENLL327.5—Unverified
3Aggressive VAENLL326.7—Unverified
#ModelMetricClaimedVerifiedStatus
1BART (TextBox 2.0)BLEU-410.2—Unverified
#ModelMetricClaimedVerifiedStatus
1STWGAN-GPBLEU-30.62—Unverified
#ModelMetricClaimedVerifiedStatus
1PALMROUGE-L41.41—Unverified
#ModelMetricClaimedVerifiedStatus
1BART (TextBox 2.0)ROUGE-L64.34—Unverified
#ModelMetricClaimedVerifiedStatus
1AEM+AttentionBLEU-114.17—Unverified
#ModelMetricClaimedVerifiedStatus
1GPT-4ASR65.1—Unverified
#ModelMetricClaimedVerifiedStatus
1BART (TextBox 2.0)ROUGE-L42.96—Unverified
#ModelMetricClaimedVerifiedStatus
1Graph2SeqBLEU22—Unverified
#ModelMetricClaimedVerifiedStatus
1WGANGP + DGflowJS-40.19—Unverified