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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 2501–2550 of 5335 papers

TitleStatusHype
End-to-End Trainable Retrieval-Augmented Generation for Relation Extraction—0
Can GPT Redefine Medical Understanding? Evaluating GPT on Biomedical Machine Reading Comprehension—0
End-to-End Segmentation-based News Summarization—0
Can GPT Improve the State of Prior Authorization via Guideline Based Automated Question Answering?—0
Are Fictional Voices Distinguishable? Classifying Character Voices in Modern Drama—0
End-to-end Image Captioning Exploits Multimodal Distributional Similarity—0
End-to-End Differentiable GANs for Text Generation—0
Can DeepSeek Reason Like a Surgeon? An Empirical Evaluation for Vision-Language Understanding in Robotic-Assisted Surgery—0
Are Current Decoding Strategies Capable of Facing the Challenges of Visual Dialogue?—0
A Probability--Quality Trade-off in Aligned Language Models and its Relation to Sampling Adaptors—0
End-to-end Concept Word Detection for Video Captioning, Retrieval, and Question Answering—0
A Generative Marker Enhanced End-to-End Framework for Argument Mining—0
End-to-end Argument Generation System in Debating—0
End-to-end argumentation knowledge graph construction—0
Can AI Read Between The Lines? Benchmarking LLMs On Financial Nuance—0
Enabling Transitivity for Lexical Inference on Chinese Verbs Using Probabilistic Soft Logic—0
CaM-Gen: Causally Aware Metric-Guided Text Generation—0
Enabling text readability awareness during the micro planning phase of NLG applications—0
Enabling Efficient On-Device Fine-Tuning of LLMs Using Only Inference Engines—0
CaM-Gen:Causally-aware Metric-guided Text Generation—0
Structured Chain-of-Thought Prompting for Code Generation—0
Enabling Language Models to Implicitly Learn Self-Improvement—0
CaM-Gen: Causally-aware Guided Text Generation—0
Call Centre Conversation Summarization: A Pilot Task at Multiling 2015—0
Architecture for a Trustworthy Quantum Chatbot—0
AfriKI: Machine-in-the-Loop Afrikaans Poetry Generation—0
A Block Metropolis-Hastings Sampler for Controllable Energy-based Text Generation—0
Empowering Backbone Models for Visual Text Generation with Input Granularity Control and Glyph-Aware Training—0
Empirical Validation of Reichenbach's Tense Framework—0
Calibrating Sequence likelihood Improves Conditional Language Generation—0
Empirical Study of Large Language Models as Automated Essay Scoring Tools in English Composition__Taking TOEFL Independent Writing Task for Example—0
Empirical Determination of Basic Heuristics for Narrative Content Planning—0
Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging—0
CaLcs: Continuously Approximating Longest Common Subsequence for Sequence Level Optimization—0
A French Corpus for Semantic Similarity—0
Emotion Style Transfer with a Specified Intensity Using Deep Reinforcement Learning—0
Emotion-Conditioned Text Generation through Automatic Prompt Optimization—0
CacheFocus: Dynamic Cache Re-Positioning for Efficient Retrieval-Augmented Generation—0
Emotion and Sentiment Guided Paraphrasing—0
A RAG-Based Institutional Assistant—0
Emotional Manipulation Through Prompt Engineering Amplifies Disinformation Generation in AI Large Language Models—0
Emotional Intelligence of Large Language Models—0
EmojiGAN: learning emojis distributions with a generative model—0
Bypassing DARCY Defense: Indistinguishable Universal Adversarial Triggers—0
A Framework for the Generation of Computer System Diagnostics in Natural Language using Finite State Methods—0
Active Learning for Natural Language Generation—0
Emerging Security Challenges of Large Language Models—0
Embodied-RAG: General Non-parametric Embodied Memory for Retrieval and Generation—0
BWArea Model: Learning World Model, Inverse Dynamics, and Policy for Controllable Language Generation—0
Embedding-Aligned Language Models—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