Working memory enables the brain to integrate transient information for rapid decision-making. Artificial networks typically replicate this via recurrent or par...
Psychological defenses are strategies, often automatic, that people use to manage distress. Rigid or overuse of defenses is negatively linked to mental health a...
Bloom filters are a fundamental data structure for approximate membership queries, with applications ranging from data analytics to databases and genomics. Seve...
We introduce Bolmo, the first family of competitive fully open byte-level language models (LMs) at the 1B and 7B parameter scales. In contrast to prior research...
Many business processes currently depend on web services, often using REST APIs for communication. REST APIs expose web service functionality through endpoints,...
The success of large language models for code relies on vast amounts of code data, including public open-source repositories, such as GitHub, and private, confi...
The use of large language models like ChatGPT in code review offers promising efficiency gains but also raises concerns about correctness and safety. Existing e...
In manufacturing, digital twins, realized as Asset Administration Shells (AAS), have emerged as a prevalent practice. These digital replicas, often utilized as ...
Reusable software components, typically distributed as packages, are a central paradigm of modern software development. The JavaScript ecosystem serves as a pri...
Ensuring the safety and reliability of Automated Driving Systems (ADS) remains a critical challenge, as traditional verification methods such as large-scale on-...
Modern data centers contain thousands of servers making them major consumers of electricity. To minimize their environmental impact, it is critical that we use ...
We present LLMQ, an end-to-end CUDA/C++ implementation for medium-sized language-model training, e.g. 3B to 32B parameters, on affordable, commodity GPUs. These...
Digital twin (DT) technology integrates heterogeneous data and models, along with semantic technologies to create multi-layered digital representation of physic...
The increasing and widespread use of BPMN business processes, also embodying DMN tables, requires tools and methodologies to verify their correctness. However, ...
Data-driven evolutionary algorithms has shown surprising results in addressing expensive optimization problems through robust surrogate modeling. Though promisi...
The pursuit of high-performance data transfer often focuses on raw network bandwidth, and international links of 100 Gbps or higher are frequently considered th...
The increasing computational demands of modern AI systems have exposed fundamental limitations of digital hardware, driving interest in alternative paradigms fo...
The innovative agriculture system is revolutionizing how we farm, making it one of the most critical innovations of our time! Yet it faces significant connectiv...
We present an oscillatory neuromorphic primitive implemented with networks of coupled Wien bridge oscillators and tunable resistive couplings. Phase relationshi...
The core challenge for streaming video generation is maintaining the content consistency in long context, which poses high requirement for the memory design. Mo...
This paper does not introduce a novel method but instead establishes a straightforward, incremental, yet essential baseline for video temporal grounding (VTG), ...
Non-parametric quantization has received much attention due to its efficiency on parameters and scalability to a large codebook. In this paper, we present a uni...
We introduce CRISP, a method that recovers simulatable human motion and scene geometry from monocular video. Prior work on joint human-scene reconstruction reli...
Universal transformers (UTs) have been widely used for complex reasoning tasks such as ARC-AGI and Sudoku, yet the specific sources of their performance gains r...
