A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Ying-Chao Ma, Anders Oland, Anton Ragni, et al.
This paper provides a comprehensive review of foundation models in music, covering representation, generative, and multimodal learning, and highlighting underexplored areas and future directions.
Bo Wen, Xin Zhang
SOLOMON is a neuro-inspired LLM reasoning network architecture that enhances domain adaptability via prompt engineering and in-context learning, outperforming baselines and matching o1-preview in semiconductor layout design.
Shriniket Dixit, Anant Kumar, Kathiravan Srinivasan, et al.
This review explores AI's contributions to improving CRISPR-based genome editing, addressing challenges like off-target effects and delivery, and discussing future research directions.
Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.
This survey systematically categorizes and reviews methods for efficient reasoning in LLMs, addressing the overthinking phenomenon by optimizing models, outputs, and input prompts.
De Jong Yeong, Gustavo Velasco-Hernandez, John M. Barry, et al.
This paper provides an end-to-end review of sensor hardware, calibration, and fusion techniques for object detection in autonomous vehicles, highlighting challenges and future research directions.
Junfei Qiu, Qihui Wu, Guoru Ding, et al.
This survey reviews machine learning techniques for big data processing, highlighting promising methods and discussing challenges, connections to signal processing, and open research trends.
Michael Hoy, Alexey S. Matveev, Andrey V. Savkin
This survey reviews collision-free navigation techniques for unmanned vehicles in unknown cluttered environments, focusing on reactive local-sensory-data methods and recent model predictive and sliding mode control laws.
Mathura Shanmugasundaram, Arunkumar Tamilarasu
This review examines the dual positive and negative impacts of digital technology, social media, and AI on cognitive functions across age groups, proposing strategies to optimize digital engagement.
Sarkar Siddique, James C. L. Chow
This topical review highlights how machine learning and AI applications in healthcare communication, including chatbots for COVID-19 education, cancer therapy, and medical imaging, can benefit humans.
Unknown
This review systematically evaluates AI4Science's progress, highlighting the shift from text-centric generation to reasoning-oriented intelligence and its challenges and perspectives.
Unknown
This paper reviews the applications, challenges, and future outlook of multimodal large language models in healthcare, emphasizing their role in integrating diverse medical data for improved clinical decision-making.
Patrick Jiang, Siru Ouyang, Yizhu Jiao, et al.
This survey systematically reviews Retrieval and Structuring Augmented Generation (RAS) methods, covering retrieval mechanisms, text structuring, and integration with LLMs, while identifying challenges and future directions.