ARCHIVES

1. T. B. Brown et al., "Language Models are Few-Shot Learners," Advances in Neural Information Processing Systems (NeurIPS), vol. 33, pp.
1877–1901, 2020.
2. R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer, "High-Resolution Image Synthesis with Latent Diffusion Models," Proc.
IEEE/CVF Conf. Computer Vision and Pattern Recognition (CVPR), pp. 10684–10695, 2022.
3. A. Ramesh et al., "Zero-Shot Text-to-Image Generation," arXiv preprint arXiv:2102.12092, 2021. [Online]. Available:
https://arxiv.org/abs/2102.12092.
4. Y. Tian, J. Zhang, Y. Wu, and X. Xue, "A Good Image Generator is What You Need for High-Resolution Video Generation," Proc. Int. Conf.
Learning Representations (ICLR), 2021. [Online]. Available: https://arxiv.org/abs/2104.15069
5. A. Shiv and C. Quirk, "Text Summarization Using Document Structure," Proc. Conf. Empirical Methods in Natural Language Processing
(EMNLP), pp. 532–541, 20196. A. Karatay and E. Hovy, "Resume Quality Assessment Using Natural Language Processing," Proc. Int. Conf. Computational Linguistics
(COLING), pp. 3191–3201, 2020.
7. L. Weidinger et al., "Ethical and Social Risks of Harm from Language Models," arXiv preprint arXiv:2112.04359, 2022. [Online]. Available:
https://arxiv.org/abs/2112.04359
8. J. W. Rae et al., "Scaling Language Models: Methods, Analysis & Insights from Training Gopher," arXiv preprint arXiv:2112.11446, 2021.
[Online]. Available: https://arxiv.org/abs/2112.11446
9. M. Chen et al., "Evaluating Large Language Models Trained on Code," arXiv preprint arXiv:2107.03374, 2021.[Online].
Available: https://arxiv.org/abs/2107.03374
10. D. Li, X. Liu, and J. Gao, "Few-Shot Learning for Multilingual Text Summarization with Pretrained Language Models," Findings of ACL:
NAACL 2022, pp. 517–530, 2022.
11. W. Xu, Y. Qian, and Y. Wu, "Automatic UI Code Generation: What’s the State of the Art?" IEEE Trans. Software Eng., vol. 48, no. 6, pp.
1699–1712, Jun. 2022.
12. Z. Lin, M. R. Lyu, and I. King, "ResumAI: A Smart Resume Generator Using GPT-Based Models," arXiv preprint arXiv:2107.11707, 2021.
[Online]. Available: https://arxiv.org/abs/2107.11707
13. S. Chopra, P. Yadav, and S. Malik, "Document Summarization and Semantic Note-Taking Using NLP," J. Information and Optimization
Sciences, vol. 42, no. 6, pp. 1443–1452, 2021.
14. A. Saxena, S. Jain, and S. Balasubramaniam, "AI-Powered Design-to-Code Conversion for Web Prototyping," Proc. ACM Conf. Human
Factors in Computing Systems (CHI EA), pp. 1–7, 2022.
15. H. K. Simonsen, "AI Text Generators and Text Producers," 2022 Int. Conf. Advanced Learning Technologies (ICALT), pp. 218–220, 2022.
16. Manjula, B. Rajashekar, T.K. Reddy, and H. Kusuma, "AI-Driven Personalized Learning and Interview Preparation," International Journal
of Scientific Research in Engineering & Technology, vol. 5, pp. –, 2024.
17. G. Manjula and G. Mahadevan, "Software Architectural Pattern to Improve the Performance and Reliability of a Business Application using
the Model View Controller," International Journal of Computer Science and Business Informatics (IJCSBI), vol. 4, no. 5, pp. –, 2023.
18. G. Manjula, K.J. Aishwarya, K.N.B. Prakash, and V.S. Chandan, "Eco-Detect: A Sustainable Solution to Advanced Waste Sorting using AI
and IoT," Proceedings of the 4th International Conference on Ubiquitous Computing and Intelligent Systems (ICUCIS), pp. –, 2024.
19. G. Manjula and G. Mahadevan, "Designing and Implementing a Scalable Chatbot Architecture using Microservices and Natural Language
Processing," International Journal of Advanced Research in Computer Science, vol. 12, no. 5, pp. 123–129, 2021.
20. G. Manjula and N. Hariprasad, "A Study on Enhancing E-Learning Systems Using AI-Based Recommendation Engines," International
Journal of Emerging Trends in Engineering Research, vol. 8, no. 6, pp. 2549–2553, 2020.