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 2701–2750 of 5335 papers

TitleStatusHype
niksss at Qur’an QA 2022: A Heavily Optimized BERT Based Model for Answering Questions from the Holy Qu’ran—0
OpenKorPOS: Democratizing Korean Tokenization with Voting-Based Open Corpus Annotation—0
Logic-Guided Message Generation from Raw Real-Time Sensor Data—0
Sentence Pair Embeddings Based Evaluation Metric for Abstractive and Extractive Summarization—0
Example-based Multilinear Sign Language Generation from a Hierarchical Representation—0
Multimodality for NLP-Centered Applications: Resources, Advances and FrontiersCode2
Barch: an English Dataset of Bar Chart Summaries—0
CLISTER : A Corpus for Semantic Textual Similarity in French Clinical Narratives—0
Generating Textual Explanations for Machine Learning Models Performance: A Table-to-Text Task—0
Lessons Learned from GPT-SW3: Building the First Large-Scale Generative Language Model for Swedish—0
Leveraging Pre-trained Language Models for Gender Debiasing—0
Décodage guidé par un discriminateur avec le Monte Carlo Tree Search pour la génération de texte contrainte (Discriminator-guided decoding with Monte Carlo Tree Search for constrained text generation )—0
Choisir le bon co-équipier pour la génération coopérative de texte (Choosing The Right Teammate For Cooperative Text Generation)—0
Romantic-Computing—0
On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic ForgettingCode1
Multi3Generation: Multitask, Multilingual, Multimodal Language Generation—0
B2T Connection: Serving Stability and Performance in Deep TransformersCode0
On the Usefulness of Embeddings, Clusters and Strings for Text Generator EvaluationCode0
CoNT: Contrastive Neural Text GenerationCode2
Controllable Text Generation with Neurally-Decomposed OracleCode1
Diffusion-LM Improves Controllable Text GenerationCode3
Quark: Controllable Text Generation with Reinforced UnlearningCode1
Understanding Metrics for Paraphrasing—0
Revisiting Generative Commonsense Reasoning: A Pre-Ordering ApproachCode0
Keywords and Instances: A Hierarchical Contrastive Learning Framework Unifying Hybrid Granularities for Text Generation—0
Gradient-Based Constrained Sampling from Language ModelsCode1
The Dialog Must Go On: Improving Visual Dialog via Generative Self-TrainingCode1
R2D2: Robust Data-to-Text with Replacement DetectionCode0
Automatic question generation based on sentence structure analysis using machine learning approach—0
Leveraging Locality in Abstractive Text SummarizationCode1
A Zipf's Law-based Text Generation Approach for Addressing Imbalance in Entity Extraction—0
PLOG: Table-to-Logic Pretraining for Logical Table-to-Text GenerationCode1
Medical Scientific Table-to-Text Generation with Human-in-the-Loop under the Data Sparsity Constraint—0
On Advances in Text Generation from Images Beyond Captioning: A Case Study in Self-Rationalization—0
Reassessing Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization—0
A Self-Paced Mixed Distillation Method for Non-Autoregressive Generation—0
BanglaNLG and BanglaT5: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in BanglaCode1
Challenges in Measuring Bias via Open-Ended Language GenerationCode0
TempLM: Distilling Language Models into Template-Based GeneratorsCode1
What Makes Data-to-Text Generation Hard for Pretrained Language Models?—0
Diversity Enhanced Table-to-Text Generation via Type Control—0
CORAL: Contextual Response Retrievability Loss Function for Training Dialog Generation Models—0
Few-Shot Natural Language Inference Generation with PDD: Prompt and Dynamic Demonstration—0
Towards Understanding Gender-Seniority Compound Bias in Natural Language GenerationCode0
Why GANs are overkill for NLP—0
Twist Decoding: Diverse Generators Guide Each OtherCode1
Learning from Bootstrapping and Stepwise Reinforcement Reward: A Semi-Supervised Framework for Text Style TransferCode0
Self-training with Two-phase Self-augmentation for Few-shot Dialogue GenerationCode0
RankGen: Improving Text Generation with Large Ranking ModelsCode1
CREATER: CTR-driven Advertising Text Generation with Controlled Pre-Training and Contrastive Fine-Tuning—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 (sample)BLEU-134.4—Unverified
2Beam search + A*esque (beam)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