The proposed LEEVLA architecture improves vision-language-action models for robotics by focusing on critical environmental changes rather than treating all visual data equally.
This survey paper categorizes and reviews recent system-level optimizations for key-value caches to improve the efficiency and throughput of large language model serving.
A new graph-based framework evaluates the logical consistency and uncertainty of large language model reasoning steps rather than just checking the final output.
A study evaluates the validity of Portugal's AMALIA language model when used as an automated data annotator for identifying moral authority.
This paper explores optimal teaching strategies for inverse reinforcement learning to help autonomous agents learn robust reward functions across multiple environments and modalities.
A new dual-system framework called FSD-VLN improves aerial vision-language navigation by separating high-level semantic reasoning from low-latency flight control.
Track2Map is a new real-time 3D Gaussian Splatting system designed to reconstruct deformable anatomy during robotic surgery without relying on precise camera trajectory priors.
Wanyun Technology has launched an automated charging service engine designed to handle complex, real-world charging scenarios across public and private sectors.
Galaxy Securities recommends that investors focus on financial performance and opportunities within the semiconductor supply chain, including memory chips and advanced packaging, amid stock market fluctuations.
Heavy-lift drones were deployed in Guangxi, China, to airlift flood victims, highlighting the growing capabilities of the country's low-altitude aviation sector.
European robotics firms are striving to remain competitive against the United States and China in the rapidly growing field of physical artificial intelligence and humanoid robotics.
The Local Linear Transformer is proposed to improve partial differential equation operator learning by addressing the quadratic scaling and lack of local bias in standard attention mechanisms.
This paper presents a neurosymbolic framework that integrates answer set programming with energy-based models to enable joint optimization in continuous latent spaces.
This study analyzes the relationship between feed-forward deep neural networks and discrete dynamical systems to offer new insights into physics-informed machine learning.
StateLinFormer is a linear-attention navigation model designed to improve long-term memory and persistent adaptation across extended interactions.
This research explores how controlling conversational timing parameters in synthetic training data affects the performance of automatic speech recognition systems.
To improve the abductive reasoning capabilities of language models, researchers created the DeepAbduction dataset and proposed a multi-perspective causal discovery method called IFAR.
CITIC Securities and CSC Financial have formed a 31-member team to guide Yangtze Memory Technologies Corp through its initial public offering process.
Shanghai-based industrial turbine developer Marvel-Tech has secured over 500 million yuan across two consecutive funding rounds led by HongShan and other venture capital firms.
South Korean financial regulators will hold a meeting to address the market impact of single-stock leveraged ETFs, which have recently experienced sharp declines.
Hugging Face has released the third part of its technical guide on profiling performance within the PyTorch framework, focusing on attention mechanisms.
An Alibaba executive emphasized that global collaboration on the open-source RISC-V chip architecture remains strong despite ongoing geopolitical tensions between the US and China.
HyperDataGrid is planning to construct a new data center facility on a former mill site near Lufkin, Texas.
NVIDIA and Hugging Face have partnered to integrate new open-source models and simulation tools into the LeRobot framework to accelerate physical AI and robotics development.