Oct 2026· Springer tracts in advanced robotics· 61 references
Smart Agriculture and AI
Abstract
Research in agricultural robotics has garnered increasing attention over the past decade. Simultaneously, Human-Robot Interaction (HRI) has emerged as a possible solution to increase automation and reduce the lack of human labor in the field. This chapter presents a study of research trends in HRI focusing on Artificial Intelligence (AI), human factors, and ergonomics in collaborative agricultural tasks. For example, we talk about the importance of robotics and the application of the different AI-based methods for HRI in field applications. Moreover, we emphasize situation awareness, stress, sleepiness, sleep quality, and distraction. We also explore various crucial and innovative topics related to HRI in agriculture, including safety, human factors, ergonomics, awareness, productivity, and management. This analysis shows that HRI paradigms can be effectively applied in agricultural applications, yielding promising production, safety, and farm management benefits, such as increasing productivity and reducing human workload.
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
An algorithm is proposed which leverages disentangled semantic factors to generate adversarial perturbation by altering controlled semantic attributes to fool the learner towards various "adversarial" targets.
Haonan Qiu, Chaowei Xiao, Lei Yang et al.· arXiv.org· 208 citations· ⚡17
This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...
Masoud Mohseni, Artur Scherer, K. Johnson et al.· arXiv.org· 121 citations· ⚡9
This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, and emerging directions from YOLOv5 through YOLO27, and examines detection, segmentation, depth, classification, pose, oriented detection, tracking, export, quantization, and deplo...
