mlsanityData to 14 Oct 2026

A Combined Encoder and Transformer Approach for Coherent and High-Quality Text Generation

arXiv 2411.12157 ↗First posted 19 Nov 2024cs.CLcited by 7

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Abstract (arXiv)

This research introduces a novel text generation model that combines BERT's semantic interpretation strengths with GPT-4's generative capabilities, establishing a high standard in generating coherent, contextually accurate language. Through the combined architecture, the model enhances semantic depth and maintains smooth, human-like text flow, overcoming limitations seen in prior models. Experimental benchmarks reveal that BERT-GPT-4 surpasses traditional models, including GPT-3, T5, BART, Transformer-XL, and CTRL, in key metrics like Perplexity and BLEU, showcasing its superior natural language generation performance. By fully utilizing contextual information, this hybrid model generates text that is not only logically coherent but also aligns closely with human language patterns, providing an advanced solution for text generation tasks. This research highlights the potential of integrating semantic understanding with advanced generative models, contributing new insights for NLP, and setting a foundation for broader applications of large-scale generative architectures in areas such as automated writing, question-answer systems, and adaptive conversational agents.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 16 of its 24 references that are in the map. First posted on arXiv 19 Nov 2024.

Builds on

16 of 24 references.

References · 16

  1. 2024Survival Prediction Across Diverse Cancer Types Using Neural Networkscited by 80
  2. 2024Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Miningcited by 47
  3. 2024Self-Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networkscited by 33
  4. 2024Thought2Text: Text Generation from EEG Signal using Large Language Models (LLMs)cited by 18
  5. 2024Emotion-Aware Interaction Design in Intelligent User Interface Using Multi-Modal Deep Learningcited by 13
  6. 2024Metric Learning for Tag Recommendation: Tackling Data Sparsity and Cold Start Issuescited by 12
  7. 2024Optimizing YOLOv5s Object Detection through Knowledge Distillation algorithmcited by 11
  8. 2024Efficient and Aesthetic UI Design with a Deep Learning-Based Interface Generation Tree Algorithmcited by 11
  9. 2024Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentationcited by 10
  10. 2024Applying Hybrid Graph Neural Networks to Strengthen Credit Risk Analysiscited by 8
  11. 2024Balancing Innovation and Privacy: Data Security Strategies in Natural Language Processing Applicationscited by 8
  12. 2024A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Miningcited by 8
4 more
  1. 2024Deep Learning for Medical Text Processing: BERT Model Fine-Tuning and Comparative Studycited by 8
  2. 2024Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysiscited by 7
  3. 2024Reinforcement Learning for Adaptive Resource Scheduling in Complex System Environmentscited by 7
  4. 2024Predicting Liquidity Coverage Ratio with Gated Recurrent Units: A Deep Learning Model for Risk Managementcited by 6

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Cited by year

Citing papers per year: 2024: 7.

7 papers.

  1. 2024An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reductioncited by 9
  2. 2024Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Datacited by 7
  3. 2024Accurate Medical Named Entity Recognition Through Specialized NLP Modelscited by 7
  4. 2024AI-Driven Health Monitoring of Distributed Computing Architecture: Insights from XGBoost and SHAPcited by 7
  5. 2024Advanced Risk Prediction and Stability Assessment of Banks Using Time Series Transformer Modelscited by 6
  6. 2024Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothingcited by 5
  7. 2024Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXtcited by 5