Knowledge catalogue
arXiv:2607.24532v1 Announce Type: new Abstract: Recent years have seen a rapid expansion in the production of large-scale geospatial maps derived from Earth observation (EO) data, driven largely by ad
arXiv:2607.23542v1 Announce Type: new Abstract: Efficient border control is becoming a significant global challenge, mainly due to severe congestion and extended passenger waiting times. To mitigate t
arXiv:2607.23967v1 Announce Type: new Abstract: Delayed generalization, or grokking, remains poorly understood despite extensive empirical study. We identify an exactly solvable late-time relaxation m
arXiv:2607.22757v1 Announce Type: cross Abstract: We introduce Graded Large Language Models (GLLMs), an algebraic framework that equips the representation space of a transformer with a grading and pro
hi everyone, im a masters student at Edinburgh Napier University and im conducting research on how Generative AI tools are being taken up across professional services (accounting, audit, law, tax and
arXiv:2607.24260v1 Announce Type: new Abstract: Modern LLM systems increasingly rely on knowledge-selection processes that produce high-value structured priors, such as ranked evidence, graph topology
arXiv:2607.24732v1 Announce Type: cross Abstract: Motivated by learning from heterogeneous and overlapping data providers, we study a stylized model of distribution learning from restricted conditiona
arXiv:2507.17636v2 Announce Type: replace Abstract: Negative campaigning is a defining feature of electoral competition, yet comparative research on its drivers has remained limited by the high cost a
arXiv:2607.18999v2 Announce Type: replace-cross Abstract: Evaluating multi-turn medical consultation agents requires judging the diagnostic support provided by the histories they elicit through intera
arXiv:2607.11094v2 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) have shown promise for solving partial differential equations (PDEs); however, their synchronous optimizati
arXiv:2607.23437v1 Announce Type: cross Abstract: We propose a neural representation for minimal surfaces. Unlike prior approaches based on discretization or Physics-Informed Neural Networks (PINNs),
Anhata Rooprai / Reuters: OpenAI and Anthropic release statements in support of the “Pacing the Frontier” initiative; Anthropic says Dario Amodei and several co-founders have signed it — More than 1,1
arXiv:2607.24345v1 Announce Type: new Abstract: Neural spectral PDE solvers often learn an entire unresolved vector field even when an inexpensive approximate model can already capture most of the tra
arXiv:2607.24199v1 Announce Type: new Abstract: Understanding and complying with traffic regulations is a safety-critical requirement for autonomous driving, yet remains challenging due to the diversi
arXiv:2601.16041v2 Announce Type: replace-cross Abstract: In constrained stochastic optimization, one expects that restricting the feasible set, provided it still contains the true parameter, should n
arXiv:2503.14549v3 Announce Type: replace-cross Abstract: How can a cheap but biased sequential, finite-horizon sampler over a discrete space be corrected so that its terminal output follows a prescri
arXiv:2607.23082v1 Announce Type: cross Abstract: The semiconductor sector faces a dual transition: scaling manufacturing execution through Artificial Intelligence (AI) while satisfying stringent sust
arXiv:2607.23634v1 Announce Type: cross Abstract: Attention enables context modeling via query-key scoring with softmax normalization. Driven by industrial long-context demands, mainstream research ha
arXiv:2607.23888v1 Announce Type: cross Abstract: In the United States, artificial intelligence (AI) is rapidly deployed amid limited federal regulation. With courts become a recurring forum in which
arXiv:2607.23642v1 Announce Type: cross Abstract: Discrete optimization algorithms are often analyzed through continuous-time limiting ODEs, but a convergence certificate for the ODE is not automatica
You patch security holes by intentionally finding them. If the models refuse to do it, how can companies protect themselves against rogue AIs, whether they are Chinese or OpenAI/Anthropic themselves?
arXiv:2607.21988v1 Announce Type: new Abstract: Self-harm content is particularly challenging to detect using NLP techniques, and is also a high-stakes task which requires the highest accuracy to enab
arXiv:2607.21980v1 Announce Type: new Abstract: Mastodon as a decentralized federation of independently moderated social servers poses unique challenges for the detection and mitigation of toxic conte
arXiv:2607.21745v1 Announce Type: cross Abstract: Radar cross-section (RCS) modeling is foundational to advancing the utility and sensitivity of spaceborne radar systems. This study introduces a deep
The National Oceanic and Atmospheric Administration (NOAA) is embarking on a transformative journey to redefine how we understand and predict patterns in the Earth’s atmosphere that affect the weather
Powered by Cohere’s secure agentic platform North, Automations enable employees, regardless of their technical abilities, to: 1. Turn complex workflows into simple outputs 2. Stay in control at each s
arXiv:2607.22534v1 Announce Type: new Abstract: Geometry Foundation Models (GFMs) have substantially advanced monocular 3D reconstruction, yet extending this capability to 4D dynamic understanding rem
arXiv:2607.22143v1 Announce Type: new Abstract: Molecular glue degraders have emerged as a promising strategy for targeted protein degradation by inducing ternary complex formation between an E3 ubiqu
Recent discussions about open-sourcing make me feel that I should go back and revisit these important open-source works in representation learning that pushed the field forward and eventually made vis
Wall Street Journal: Sources: Nvidia is in talks to provide a ~$250B backstop for OpenAI as part of a 10 GW data center project that SoftBank is developing in Ohio — Project would be one of the larges
arXiv:2607.21558v1 Announce Type: new Abstract: Building socially calibrated large language models, which can learn from others without simply yielding to them, requires more than reducing sycophancy
arXiv:2607.20737v1 Announce Type: new Abstract: Graph Neural Networks trained on heterogenous bipartite graphs form a common basis in recommendation systems. These graphs often express relations that
arXiv:2412.01748v2 Announce Type: replace Abstract: Complex dynamical systems, such as particle accelerators, often require intricate and time-consuming tuning procedures to achieve optimal performanc
arXiv:2607.21444v1 Announce Type: cross Abstract: Reliable electric vehicle (EV) charging infrastructure is a cornerstone of sustainable, low-carbon cities, yet urban climate stress such as extreme he
arXiv:2607.20527v1 Announce Type: new Abstract: Agentic LLM systems such as OpenScholar and PaperQA2 read the scientific literature and return cited answers, and both they and their benchmarks already
arXiv:2606.14502v2 Announce Type: replace Abstract: Large Language Models (LLMs) are undergoing a fundamental transformation from conversational generators into integrated AI systems capable of reason
arXiv:2607.21327v1 Announce Type: cross Abstract: Bibliometric indicators - citation counts, h-indexes, co-authorship networks - have long anchored science, technology, and innovation (STI) analytics,
arXiv:2607.21353v1 Announce Type: new Abstract: Machine unlearning aims to remove the influence of specific training data while preserving model utility. Many state-of-the-art approaches pursue this g
arXiv:2607.20542v1 Announce Type: cross Abstract: A critical challenge in healthcare systems in low- and middle-income countries (LMICs) is the efficient and equitable allocation of scarce resources,
Introducing Claude Opus 5 I've been offline kayaking with sea otters for much of today so I haven't had a chance to put Anthropic's new model Claude Opus 5 through its paces yet. The buzz is positive,
arXiv:2607.20427v1 Announce Type: cross Abstract: Mixture-of-Experts architectures have revolutionized scaling, yet the underlying logic of their routing remains a black box. In this paper, we uncover
arXiv:2607.20872v1 Announce Type: new Abstract: Long-form legal research reports increasingly rely on LLMs and agentic research systems, but their reliability depends not only on answering the task, b
arXiv:2601.21284v2 Announce Type: replace-cross Abstract: Diffusion models have emerged as powerful generative tools for modeling complex data distributions, yet their purely data-driven nature limits
arXiv:2607.20451v1 Announce Type: new Abstract: Semantic Field Theory (SFT) has developed from a philosophical critique of strong anti-formalist readings of language games into a proposed computationa
arXiv:2607.20587v1 Announce Type: cross Abstract: Modern power systems increasingly require probabilistic forecasts amid interacting uncertainties from renewable intermittency, flexible demand, market
arXiv:2607.20781v1 Announce Type: new Abstract: Artificial Intelligence (AI) is rapidly transforming organizations, raising a fundamental organizational and economic question: when will a human employ
arXiv:2607.21495v1 Announce Type: new Abstract: AI agents are increasingly created inside organizations by non-engineering users through low-code, no-code, and conversational development environments.
arXiv:2607.20778v1 Announce Type: new Abstract: Weather forecasting foundation models (FMs) are increasingly fine-tuned to predict air quality, offering fast global pollution forecasts at lower comput
arXiv:2607.19315v1 Announce Type: new Abstract: We propose the effective rank (ERank) of the channel covariance of an image's deep feature map as a per-sample, label-free measure of visual richness, c
arXiv:2607.19038v1 Announce Type: new Abstract: Translating novels into films poses a grand challenge for generative artificial intelligence, requiring conversion of abstract literary prose into long-
arXiv:2607.19449v1 Announce Type: cross Abstract: Evaluation frameworks for tool-augmented LLM agents focus overwhelmingly on capability metrics or explicit tool crashes, leaving silent infrastructure
Frontier AI models are increasingly demonstrating high‑risk autonomous behaviours that pose safety threats. Incidents such as OpenAI‑released models escaping containment safeguards and a Hugging Face
arXiv:2607.19628v1 Announce Type: new Abstract: In this work we investigate reinforcement learning (RL) as a framework for the robust control of parametrized dynamical systems in presence of measureme
arXiv:2607.18787v1 Announce Type: new Abstract: We investigate whether a pretrained generative image-editing model can provide a common interface for numerical simulation. Physical inputs and solution
On July 23, 2026, a Polymarket tweet announced that Anthropic donated $20 million to a political nonprofit calling for stricter AI regulation ahead of the U.S. midterm elections. The post, posted at 4
arXiv:2607.20321v1 Announce Type: cross Abstract: Neural surrogates are widely used in scientific machine learning for fast prediction of three-dimensional (3D) thermo-fluid fields. However, generatin
arXiv:2607.18924v1 Announce Type: new Abstract: Recent advances in image-to-video generation have improved visual realism, making physically grounded and controllable dynamics an important step toward
arXiv:2607.19360v1 Announce Type: new Abstract: Large language models (LLMs) often answer queries by mapping individual observations to more general rule-like structures. However, it remains unclear h
The news about Anthropic settling a class action lawsuit for 1.5B over training data isn't just a legal headache for them, it's a massive warning sign for engineering teams relying entirely on closed
arXiv:2607.17967v2 Announce Type: replace Abstract: Monocular geometry estimation has recently achieved impressive performance across diverse scenes. However, state-of-the-art models still face notabl