This research investigates the use of large language models (LLMs) in software penetration testing (pentesting) to identify security vulnerabilities in source code. The authors hypothesize that an LLM-based AI agent…
Continue readingThe article ‘Towards Goal-oriented Large Language Model Prompting: A Survey’ by Haochen Li, Jonathan Leung, and Zhiqi Shen focuses on the limitations of current prompt engineering methods for Large Language…
Continue readingThe article discusses the significant progress in Natural Language Processing (NLP), focusing on Large Language Models (LLM) and prompt engineering techniques. The authors discuss the use of reasoning topologies like…
Continue readingThe article ‘Prompt Smells: An Omen for Undesirable Generative AI Outputs’ discusses the recent trends in Generative Artificial Intelligence (GenAI) and its application in various fields. It sheds light on…
Continue readingThe paper addresses the issue of distributional shift in machine learning models, especially in text-to-audio generation. The authors observe a consistent audio quality degradation in generated audio samples with user…
Continue readingThe research paper discusses the challenge in text-to-audio (TTA) generation, particularly the issue of under-specified user prompts when compared to the training text descriptions. The authors treat TTA models as…
Continue readingThe article by Damien Masson et al. presents DirectGPT, an interface layer on top of ChatGPT, designed to improve the interaction with large language models (LLMs). The authors argue that…
Continue readingThis paper provides a comprehensive survey of prompt engineering on three types of vision-language models: multimodal-to-text generation models, image-text matching models, and text-to-image generation models. Prompt engineering, the technique of…
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