A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Yuri Kuratov, A. Bulatov, Petr Anokhin, et al.
Recurrent memory augmentation enables GPT-2 to process sequences up to 11 million elements, far exceeding standard methods limited to 10,000 elements.
Hanzhuo Tan, Qi Luo, Jing Li, et al.
LLM4Decompile is the first open-source LLM series trained to decompile binary code, outperforming GPT-4o and Ghidra by over 100% in re-executability.
W. Yeadon, Alex Peach, Craig P. Testrow
Evaluates ChatGPT variants on university-level physics coding assignments, finding students outperform AI and human evaluators detect AI work with 85.3% accuracy.
Zhengren Wang, Jiayang Yu, Dongsheng Ma, et al.
RARE decouples knowledge storage from reasoning by externalizing domain knowledge to retrievable sources and internalizing reasoning patterns, enabling lightweight models to surpass GPT-4 and DeepSeek-R1 by ~20% accuracy.
Gokul Yenduri, M. Ramalingam, G. Chemmalar Selvi, et al.
A comprehensive review of GPT covering architecture, training, enabling technologies, applications, challenges, and future directions.
Michael Dowling, Brian M. Lucey
ChatGPT can assist finance research by generating ideas and identifying data, but is weaker on literature synthesis and testing frameworks, with output quality depending on private data and domain expertise.
Steffen Herbold, Annette Hautli-Janisz, Ute Heuer, et al.
A large-scale study comparing human-written and ChatGPT-generated argumentative essays finds AI essays rated higher in quality by teachers, with distinct linguistic characteristics.
Katharina Jeblick, Balthasar Schachtner, Jakob Dexl, et al.
This exploratory case study evaluates the quality of simplified radiology reports generated by ChatGPT, finding that while most radiologists rated them factually correct and complete, instances of errors and potential harm remain.
Maanak Gupta, Charankumar Akiri, Kshitiz Aryal, et al.
This paper explores the dual-use of generative AI in cybersecurity, demonstrating attack techniques like jailbreaks and prompt injection, while also proposing defensive applications.
Volker Bilgram, Felix Laarmann
Generative AI, particularly LLMs like GPT, can augment early innovation phases—exploration, ideation, and digital prototyping—by enabling faster iterations and reduced costs.
Humaid Al Naqbi, Zied Bahroun, Vian Ahmed
A PRISMA-based literature review of 159 papers analyzing how generative AI enhances productivity across multiple sectors, with bibliometric identification of ChatGPT as a dominant tool.
Yan Hu, Qingyu Chen, Jingcheng Du, et al.
This paper shows that task-specific prompt engineering, incorporating medical knowledge and few-shot examples, significantly improves GPT-3.5 and GPT-4 performance on clinical NER tasks, though still below BioClinicalBERT.