A review of large language models and autonomous agents in chemistry
Large language models (LLMs) have emerged as powerful tools in chemistry, significantly
impacting molecule design, property prediction, and synthesis optimization. This review …
impacting molecule design, property prediction, and synthesis optimization. This review …
A comprehensive survey of foundation models in medicine
Foundation models (FMs) are large-scale deeplearning models that are developed using
large datasets and self-supervised learning methods. These models serve as a base for …
large datasets and self-supervised learning methods. These models serve as a base for …
Survey of different large language model architectures: Trends, benchmarks, and challenges
Large Language Models (LLMs) represent a class of deep learning models adept at
understanding natural language and generating coherent responses to various prompts or …
understanding natural language and generating coherent responses to various prompts or …
Elecbench: a power dispatch evaluation benchmark for large language models
In response to the urgent demand for grid stability and the complex challenges posed by
renewable energy integration and electricity market dynamics, the power sector increasingly …
renewable energy integration and electricity market dynamics, the power sector increasingly …
Acceleration for Deep Reinforcement Learning using Parallel and Distributed Computing: A Survey
Deep reinforcement learning has led to dramatic breakthroughs in the field of artificial
intelligence for the past few years. As the amount of rollout experience data and the size of …
intelligence for the past few years. As the amount of rollout experience data and the size of …
LLM-based framework for bearing fault diagnosis
L Tao, H Liu, G Ning, W Cao, B Huang, C Lu - Mechanical Systems and …, 2025 - Elsevier
Accurately diagnosing bearing faults is crucial for maintaining the efficient operation of
rotating machinery. However, traditional diagnosis methods face challenges due to the …
rotating machinery. However, traditional diagnosis methods face challenges due to the …
Large language models orchestrating structured reasoning achieve kaggle grandmaster level
We introduce Agent K v1. 0, an end-to-end autonomous data science agent designed to
automate, optimise, and generalise across diverse data science tasks. Fully automated …
automate, optimise, and generalise across diverse data science tasks. Fully automated …
Integrating reinforcement learning and large language models for crop production process management optimization and control through a new knowledge-based …
D Chen, Y Huang - Computers and Electronics in Agriculture, 2025 - Elsevier
Efficient and sustainable crop production process management is crucial to meet the
growing global demand for food, fuel, and feed while minimizing environmental impacts …
growing global demand for food, fuel, and feed while minimizing environmental impacts …
Reinforcement learning: An overview
K Murphy - arxiv preprint arxiv:2412.05265, 2024 - arxiv.org
This manuscript gives a big-picture, up-to-date overview of the field of (deep) reinforcement
learning and sequential decision making, covering value-based RL, policy-gradient …
learning and sequential decision making, covering value-based RL, policy-gradient …
iLLM-TSC: Integration reinforcement learning and large language model for traffic signal control policy improvement
Urban congestion remains a critical challenge, with traffic signal control (TSC) emerging as
a potent solution. TSC is often modeled as a Markov Decision Process problem and then …
a potent solution. TSC is often modeled as a Markov Decision Process problem and then …