With the intensified exploration of marine resources, marine bioactive peptides have become one of the research focuses in biomedicine, food science, and materials science because of their structural ...
Large Reasoning Models (LRMs) achieve strong accuracy on challenging tasks by generating long Chain-of-Thought traces, but suffer from overthinking. Even after reaching the correct answer, they contin...
Microplastic (MP) contamination is a notable environmental challenge affecting marine ecosystems. However, its repercussions on the reproductive success of sea turtles remain inadequately elucidated. ...
Quantum machine learning is a promising paradigm for learning from limited data, a central bottleneck in domains such as medical imaging, clinical trials, and rare diseases. Quantum convolutional neur...
Habitat condition and area shape global species distributions, with shallow-water reefs hosting a disproportional share of marine biodiversity. Although reef area is a well-established predictor of ma...
It is estimated that millions of species exist in the deep-sea environment, such as hydrothermal vents, cold seeps, abyssal plains and seamounts, which have yet to be described. Non-invasive biodivers...
The North Equatorial Recirculation Region (NERR) in the northern tropical Atlantic functions as the region of origin of the recurring large-scale blooms of pelagic Sargassum spp. that have occurred si...
Accurate motion prediction of floating platforms is critical for ensuring operational safety in offshore engineering applications or marine equipment testing. However, the strong nonlinearity and non-...
Large language model (LLM) agents increasingly automate multi-step engineering and informatics workflows, yet they rarely ask how much effort a task actually requires. They often follow a maximum-cont...
Eco-engineering practices are increasingly implemented in urbanised marine coastal zones to enhance local marine biodiversity, as part of biodiversity offsetting efforts in areas impacted by human act...
Background: The mechanisms underlying central nervous system oxygen toxicity (CNS-OT), which manifests as generalized seizures, remain poorly understood, thereby limiting the utility of hyperbaric oxy...
Despite receiving significant interest from the biological and engineering communities, several questions about the underlying reasons for the form of the deep-sea sponge Venus flower basket (Euplecte...
Social media can reveal patient experiences with glucagon-like peptide-1 receptor agonists (GLP-1 RAs) that extend beyond clinical trial data. We analyzed 410,198 Reddit posts (May 2019-June 2025) men...
Penetration testing, the practice of simulating cyberattacks to identify vulnerabilities, is a complex sequential decision-making task that is inherently partially observable and features large action...
The key-value (KV) cache is widely treated as essential state in transformer inference, and a large body of work engineers policies to compress, evict, or approximate its entries. We prove that this s...
Large language models (LLMs) are increasingly used to answer natural-language questions over structured data. However, when a table contains familiar real-world facts, it is unclear whether the model ...
Protein sequence optimization under tight oracle budgets requires methods that explore vast combinatorial spaces while making each evaluation informative. Existing reinforcement learning and off-polic...
The collective movement of stock prices harbors complex interdependencies that are conventionally simplified only through a linear lens. This paper explores computed structural network representations...
Evaluating an AI system requires disaggregated assessment, as performance varies across domains such as benchmark task types or conversation types in deployed agents. Exhaustive testing is expensive, ...
Understanding how training data shape neural network predictions is a central problem in modern learning theory. In 2020, Pedro Domingos proposed an interpolation formula valid for every model learned...
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