Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.
arXiv:2608. 13944v1 Announce Type: cross Abstract: This paper examines a use of AI in creative practice as an interpretive sounding board for human-generated material, rather than the more familiar pattern of AI generation followed by human curation.
arXiv:2608. 14015v1 Announce Type: cross Abstract: Understanding tens-of-minutes surgical videos requires long-horizon temporal reasoning, answering what happens before, after, or across stages of a procedure by grounding the question in visual evidence spread across time.
arXiv:2608. 14094v1 Announce Type: cross Abstract: Cloud-local LLM inference systems have the potential to use the reasoning capability of large cloud models while protecting sensitive user data on personal devices.
arXiv:2608. 14264v1 Announce Type: cross Abstract: Model merging combines trained models directly in weight space, offering a compute-efficient alternative to additional fine-tuning.
arXiv:2608. 14286v1 Announce Type: cross Abstract: Vision language models (VLMs) are increasingly used in industrial decision-making systems, such as recruitment support and recommendation.
arXiv:2608. 14370v1 Announce Type: cross Abstract: The modelling and analysis of secure business processes require the incorporation of security annotations into process models.
arXiv:2608. 14505v1 Announce Type: cross Abstract: Recipe data arises in domains such as materials synthesis, pharmaceutical formulation, and industrial manufacturing, where procedures are represented as ordered sequences of steps containing heterogeneous structured fields.
arXiv:2603. 18871v2 Announce Type: replace Abstract: Urban Vehicular Ad-Hoc Networks (VANETs) can become fragmented because buildings obstruct wireless links and vehicle mobility continuously changes the network topology.
arXiv:1912. 08786v3 Announce Type: replace-cross Abstract: Three generations of software have transformed the role of artificial intelligence in society.
arXiv:2402. 01591v4 Announce Type: replace-cross Abstract: Spatial sound reasoning is a fundamental human skill, enabling us to navigate and interpret our surroundings based on sound.
arXiv:2402. 01826v2 Announce Type: replace-cross Abstract: Current blood pressure (BP) technologies and standards were established decades ago, and these standards are still used worldwide today, often without adjusting BP readings for individual demographic factors such as sex and age.
arXiv:2503. 01236v3 Announce Type: replace-cross Abstract: This paper addresses fixed-graph terrain-aware path refinement, in which a global planner is restricted to a predefined route space and may remain optimal within that space while missing lower-cost terrain corridors available in the native-resolution map.
arXiv:2508. 16131v3 Announce Type: replace-cross Abstract: Code completion entails the task of providing missing tokens given a surrounding context.
arXiv:2512. 14732v3 Announce Type: replace-cross Abstract: Incidental findings in CT scans, though often benign, can have significant clinical implications and should be reported following established guidelines.
arXiv:2608. 01014v2 Announce Type: replace-cross Abstract: Preference optimization improves mathematical reasoning in large language models (LLMs), but reliable chosen-rejected pairs usually require verified answers, human annotations, or external reward models.
arXiv:2608. 14186v1 Announce Type: new Abstract: Tabular anomaly detection is dominated by classical density-proxy methods (Isolation Forest, OCSVM, LOF), reconstruction-based detectors (Autoencoders, VAEs), and modern non-parametric scorers (COPOD, ECOD, Deep SVDD), all of which approximate the inlier distribution only indirectly; explicit energy-based models are largely absent.
arXiv:2608. 14191v1 Announce Type: new Abstract: The key-value (KV) cache stores information from past tokens and is a major memory bottleneck in long-context inference.
arXiv:2608. 14198v1 Announce Type: new Abstract: Banks analyse sequential financial transaction data to perform many tasks, including fraud prevention, credit risk assessment and offer personalization.
arXiv:2608. 14303v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for code generation, yet they remain vulnerable to prompts that elicit insecure implementations.
arXiv:2608. 14349v1 Announce Type: new Abstract: We present a training-free method for multi-modal trajectory prediction that achieves comparable accuracy to a 57M-parameter transformer while requiring no GPU and zero learned parameters.