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Large language models (LLMs) are rapidly transforming materials science. This review examines recent LLM applications across the materials discovery pipeline, focusing on three key areas: mining scientific literature , predictive modelling,…

Computation and Language · Computer Science 2025-11-17 Fengxu Yang , Weitong Chen , Jack D. Evans

Recent advances in artificial intelligence have witnessed the emergence of large-scale deep learning models capable of interpreting and generating both textual and imaging data. Such models, typically referred to as foundation models, are…

This work presents an analytical framework for the design and analysis of LLM-based algorithms, i.e., algorithms that contain one or multiple calls of large language models (LLMs) as sub-routines and critically rely on the capabilities of…

Machine Learning · Computer Science 2025-10-14 Yanxi Chen , Yaliang Li , Bolin Ding , Jingren Zhou

The rise of foundation models has transformed machine learning research, prompting efforts to uncover their inner workings and develop more efficient and reliable applications for better control. While significant progress has been made in…

The advent of foundation models has revolutionized the fields of natural language processing and computer vision, paving the way for their application in autonomous driving (AD). This survey presents a comprehensive review of more than 40…

Machine Learning · Computer Science 2024-09-06 Haoxiang Gao , Zhongruo Wang , Yaqian Li , Kaiwen Long , Ming Yang , Yiqing Shen

Advances in machine learning over the past decade have resulted in a proliferation of algorithmic applications for encoding, characterizing, and acting on complex data that may contain many high dimensional features. Recently, the emergence…

The development of automated experimental facilities and the digitization of experimental data have introduced numerous opportunities to radically advance chemical laboratories. As many laboratory tasks involve predicting and understanding…

Foundation models (FMs) are recognized as a transformative breakthrough that has started to reshape the future of artificial intelligence (AI) across both academia and industry. The integration of FMs into wireless networks is expected to…

Networking and Internet Architecture · Computer Science 2026-01-07 Han Zhang , Mohammad Farzanullah , Mohammad Ghassemi , Akram Bin Sediq , Ali Afana , Melike Erol-Kantarci

Materials discovery and development are critical for addressing global challenges. Yet, the exponential growth in materials science literature comprising vast amounts of textual data has created significant bottlenecks in knowledge…

Large Language Models (LLMs) have become a milestone in the field of artificial intelligence and natural language processing. However, their large-scale deployment remains constrained by the need for significant computational resources.…

Computation and Language · Computer Science 2025-08-07 Julián Camilo Velandia Gutiérrez

Building general-purpose robots that operate seamlessly in any environment, with any object, and utilizing various skills to complete diverse tasks has been a long-standing goal in Artificial Intelligence. However, as a community, we have…

With the emergence of Large Language Models (LLMs) and Vision Foundation Models (VFMs), multimodal AI systems benefiting from large models have the potential to equally perceive the real world, make decisions, and control tools as humans.…

We study the use of large language models (LLMs) for physics instrument design and compare their performance to reinforcement learning (RL). Using only prompting, LLMs are given task constraints and summaries of prior high-scoring designs…

Instrumentation and Detectors · Physics 2026-01-13 Sara Zoccheddu , Shah Rukh Qasim , Patrick Owen , Nicola Serra

The human ability to learn, generalize, and control complex manipulation tasks through multi-modality feedback suggests a unique capability, which we refer to as dexterity intelligence. Understanding and assessing this intelligence is a…

Robotics · Computer Science 2025-12-03 Fanlong Zeng , Wensheng Gan , Zezheng Huai , Lichao Sun , Hechang Chen , Yongheng Wang , Ning Liu , Philip S. Yu

Active learning (AL) accelerates scientific discovery by prioritizing the most informative experiments, but traditional machine learning (ML) models used in AL suffer from cold-start limitations and domain-specific feature engineering,…

Machine Learning · Computer Science 2025-12-05 Hongchen Wang , Rafael Espinosa Castañeda , Jay R. Werber , Yao Fehlis , Edward Kim , Jason Hattrick-Simpers

Large Language Models (LLMs) have garnered considerable interest due to their impressive natural language capabilities, which in conjunction with various emergent properties make them versatile tools in workflows ranging from complex code…

Materials Science · Physics 2024-10-22 Ge Lei , Ronan Docherty , Samuel J. Cooper

Humans possess an extraordinary ability to create and utilize tools, allowing them to overcome physical limitations and explore new frontiers. With the advent of foundation models, AI systems have the potential to be equally adept in tool…

Recent large language models (LLMs) have demonstrated promising capabilities in modeling real-world knowledge and enhancing knowledge-based generation tasks. In this paper, we further explore the potential of using LLMs to aid in the design…

Robotics · Computer Science 2024-11-04 Weicheng Ma , Luyang Zhao , Chun-Yi She , Yitao Jiang , Alan Sun , Bo Zhu , Devin Balkcom , Soroush Vosoughi

Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing daily life through their exceptional language understanding and contextual generation capabilities. Despite their remarkable performance, LLMs…

Artificial Intelligence · Computer Science 2024-12-10 Yedi Zhang , Yufan Cai , Xinyue Zuo , Xiaokun Luan , Kailong Wang , Zhe Hou , Yifan Zhang , Zhiyuan Wei , Meng Sun , Jun Sun , Jing Sun , Jin Song Dong