SOTAVerified

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 4451–4500 of 5335 papers

TitleStatusHype
Scalable Micro-planned Generation of Discourse from Structured DataCode0
Findings of the E2E NLG Challenge—0
Frustratingly Easy Model Ensemble for Abstractive Summarization—0
Automatic Essay Scoring Incorporating Rating Schema via Reinforcement Learning—0
Similarity-Based Reconstruction Loss for Meaning Representation—0
Sounds Wilde. Phonetically Extended Embeddings for Author-Stylized Poetry Generation—0
Diversity-Promoting GAN: A Cross-Entropy Based Generative Adversarial Network for Diversified Text GenerationCode0
Sentence Compression for Arbitrary Languages via Multilingual PivotingCode0
Meteor++: Incorporating Copy Knowledge into Machine Translation Evaluation—0
Learning Latent Semantic Annotations for Grounding Natural Language to Structured DataCode0
EmojiGAN: learning emojis distributions with a generative model—0
Deep Attentive Sentence Ordering Network—0
Boosting Text Classification Performance on Sexist Tweets by Text Augmentation and Text Generation Using a Combination of Knowledge Graphs—0
MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling—0
Curriculum Learning Based on Reward Sparseness for Deep Reinforcement Learning of Task Completion Dialogue Management—0
CaLcs: Continuously Approximating Longest Common Subsequence for Sequence Level Optimization—0
Incorporating Background Knowledge into Video Description Generation—0
Improving Neural Abstractive Document Summarization with Structural Regularization—0
Improving Neural Abstractive Document Summarization with Explicit Information Selection Modeling—0
Training for Diversity in Image Paragraph CaptioningCode0
QuaSE: Sequence Editing under Quantifiable GuidanceCode0
AirDialogue: An Environment for Goal-Oriented Dialogue ResearchCode0
Operation-guided Neural Networks for High Fidelity Data-To-Text Generation—0
Generating Classical Chinese Poems via Conditional Variational Autoencoder and Adversarial Training—0
Generating Syntactic Paraphrases—0
Text Morphing—0
SALSA-TEXT : self attentive latent space based adversarial text generation—0
GraphSeq2Seq: Graph-Sequence-to-Sequence for Neural Machine Translation—0
Hierarchically-Structured Variational Autoencoders for Long Text Generation—0
TopicGAN: Unsupervised Text Generation from Explainable Latent Topics—0
Discrete Structural Planning for Generating Diverse Translations—0
A bird's eye view on coherence, and a worm's eye view on cohesion—0
Differentiable Expected BLEU for Text Generation—0
Fast and Simple Mixture of Softmaxes with BPE and Hybrid-LightRNN for Language GenerationCode0
Sentence-Level Fluency Evaluation: References Help, But Can Be Spared!—0
Investigating Linguistic Pattern Ordering in Hierarchical Natural Language GenerationCode0
Adversarial Text Generation via Feature-Mover's DistanceCode0
SQL-to-Text Generation with Graph-to-Sequence ModelCode0
Characterizing Variation in Crowd-Sourced Data for Training Neural Language Generators to Produce Stylistically Varied Outputs—0
End-to-end Image Captioning Exploits Multimodal Distributional Similarity—0
Operations Guided Neural Networks for High Fidelity Data-To-Text GenerationCode0
Top-down Tree Structured Decoding with Syntactic Connections for Neural Machine Translation and Parsing—0
Describing a Knowledge BaseCode0
Data-to-Text Generation with Content Selection and PlanningCode0
A Structured Review of the Validity of BLEU—0
When to Finish? Optimal Beam Search for Neural Text Generation (modulo beam size)—0
Learning Neural Templates for Text GenerationCode0
Guided Neural Language Generation for Abstractive Summarization using Abstract Meaning RepresentationCode0
Multi-Reference Training with Pseudo-References for Neural Translation and Text Generation—0
Natural Language Generation with Neural Variational ModelsCode0
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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