Long Form Novel
Long-form novel generation is a challenging area of artificial intelligence research focused on creating coherent and engaging narratives of substantial length. Current research emphasizes hierarchical frameworks, often incorporating large language models (LLMs) and techniques like prompt learning, to improve plot coherence, character development, and overall narrative quality. These advancements leverage various neural network architectures, including transformers and convolutional neural networks, and explore novel approaches such as data augmentation and knowledge transfer to enhance model performance. The development of robust and creative long-form text generation has significant implications for creative writing, storytelling, and other applications requiring the generation of complex and lengthy textual content.
Papers
Enhancing Plant Disease Detection: A Novel CNN-Based Approach with Tensor Subspace Learning and HOWSVD-MD
Abdelmalik Ouamane, Ammar Chouchane, Yassine Himeur, Abderrazak Debilou, Abbes Amira, Shadi Atalla, Wathiq Mansoor, Hussain Al Ahmad
GKT: A Novel Guidance-Based Knowledge Transfer Framework For Efficient Cloud-edge Collaboration LLM Deployment
Yao Yao, Zuchao Li, Hai Zhao