Forecasting Russian Equipment Losses Using Time Series and Deep Learning Models
arXiv:2509.07813v1 Announce Type: cross Abstract: This study applies a range of forecasting techniques,including ARIMA, Prophet, Long Short Term Memory networks…
arXiv:2509.07813v1 Announce Type: cross Abstract: This study applies a range of forecasting techniques,including ARIMA, Prophet, Long Short Term Memory networks…
arXiv:2410.07553v3 Announce Type: replace Abstract: The rapid advances of multimodal agents built on large foundation models have largely overlooked their…
arXiv:2508.00103v3 Announce Type: replace-cross Abstract: This study explores the integration of Augmented Intelligence (AuI) in Intelligent Tutoring Systems (ITS) to…
arXiv:2509.07571v1 Announce Type: cross Abstract: The rapid advancement of large language models (LLMs) and domain-specific AI agents has greatly expanded…
arXiv:2509.05388v1 Announce Type: cross Abstract: Cell biomechanics involve a great number of complex phenomena that are fundamental to the evolution…
arXiv:2509.06326v1 Announce Type: cross Abstract: As on-device LLMs(e.g., Apple on-device Intelligence) are widely adopted to reduce network dependency, improve privacy,…
arXiv:2509.06475v1 Announce Type: cross Abstract: AI-based recommender systems increasingly influence recruitment decisions. Thus, transparency and responsible adoption in Human Resource…
arXiv:2509.05218v2 Announce Type: replace-cross Abstract: Positional encoding mechanisms enable Transformers to model sequential structure and long-range dependencies in text. While…
arXiv:2509.04537v2 Announce Type: replace-cross Abstract: We investigate the emergent social dynamics of Large Language Model (LLM) agents in a spatially…
arXiv:2509.02640v2 Announce Type: replace-cross Abstract: Atypical mitotic figures (AMFs) are clinically relevant indicators of abnormal cell division, yet their reliable…