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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 3101–3150 of 5335 papers

TitleStatusHype
Grounding in social media: An approach to building a chit-chat dialogue model—0
Why is constrained neural language generation particularly challenging?—0
Bridging the Gap Between Training and Inference of Bayesian Controllable Language Models—0
The Case for a Single Model that can Both Generate Continuations and Fill in the Blank—0
LegoNN: Building Modular Encoder-Decoder Models—0
Enhancing Dual-Encoders with Question and Answer Cross-Embeddings for Answer Retrieval—0
A Benchmark for Federated Hetero-Task Learning—0
Curriculum-Based Self-Training Makes Better Few-Shot Learners for Data-to-Text GenerationCode0
Understanding EFL Student Idea Generation Strategies for Creative Writing with NLG Tools—0
Automatic Generation of Programming Exercises and Code Explanations using Large Language Models—0
Disentangled Generation Network for Enlarged License Plate Recognition and A Unified Dataset—0
CLISTER : A Corpus for Semantic Textual Similarity in French Clinical Narratives—0
niksss at Qur’an QA 2022: A Heavily Optimized BERT Based Model for Answering Questions from the Holy Qu’ran—0
Multi3Generation: Multitask, Multilingual, Multimodal Language Generation—0
Barch: an English Dataset of Bar Chart Summaries—0
Logic-Guided Message Generation from Raw Real-Time Sensor Data—0
Leveraging Pre-trained Language Models for Gender Debiasing—0
Example-based Multilinear Sign Language Generation from a Hierarchical Representation—0
B2T Connection: Serving Stability and Performance in Deep TransformersCode0
Romantic-Computing—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
OpenKorPOS: Democratizing Korean Tokenization with Voting-Based Open Corpus Annotation—0
Sentence Pair Embeddings Based Evaluation Metric for Abstractive and Extractive Summarization—0
Choisir le bon co-équipier pour la génération coopérative de texte (Choosing The Right Teammate For Cooperative Text Generation)—0
Generating Textual Explanations for Machine Learning Models Performance: A Table-to-Text Task—0
Handling Idioms in Symbolic Multilingual Natural Language Generation—0
Lessons Learned from GPT-SW3: Building the First Large-Scale Generative Language Model for Swedish—0
On the Usefulness of Embeddings, Clusters and Strings for Text Generator EvaluationCode0
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
A Zipf's Law-based Text Generation Approach for Addressing Imbalance in Entity Extraction—0
Automatic question generation based on sentence structure analysis using machine learning approach—0
R2D2: Robust Data-to-Text with Replacement DetectionCode0
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
Challenges in Measuring Bias via Open-Ended Language GenerationCode0
What Makes Data-to-Text Generation Hard for Pretrained Language Models?—0
A Self-Paced Mixed Distillation Method for Non-Autoregressive Generation—0
Diversity Enhanced Table-to-Text Generation via Type Control—0
Few-Shot Natural Language Inference Generation with PDD: Prompt and Dynamic Demonstration—0
CORAL: Contextual Response Retrievability Loss Function for Training Dialog Generation Models—0
Why GANs are overkill for NLP—0
Learning from Bootstrapping and Stepwise Reinforcement Reward: A Semi-Supervised Framework for Text Style TransferCode0
Towards Understanding Gender-Seniority Compound Bias in Natural Language GenerationCode0
Self-training with Two-phase Self-augmentation for Few-shot Dialogue GenerationCode0
CREATER: CTR-driven Advertising Text Generation with Controlled Pre-Training and Contrastive Fine-Tuning—0
Classifiers are Better Experts for Controllable Text Generation—0
Mitigating Toxic Degeneration with Empathetic Data: Exploring the Relationship Between Toxicity and Empathy—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