Knowledge catalogue
arXiv:2608.14999v1 Announce Type: cross Abstract: Constructing special graphs is an important task within graph theory and computer science. Many popular graph constructions are the result of a compre
arXiv:2608.15598v1 Announce Type: cross Abstract: Underwater color restoration promises to unlock color as a reliable signal for aquatic sciences, but achieving this with scientific confidence remains
Announcing AItonomy Foundation. We are PhD students and postdocs at Stanford, Princeton and Oxford, building a nonprofit research organization for AI4Science and Science4AI — and connecting early-care
arXiv:2404.02692v3 Announce Type: replace-cross Abstract: The explosion of data available in life sciences is fueling an increasing demand for expressive models and computational methods. Graph transf
arXiv:2608.14228v1 Announce Type: new Abstract: Life science knowledge graphs make large collections of structured data available through SPARQL, but each resource uses its own schema, identifiers, an
arXiv:2608.14152v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have reshaped semantic analysis. Opinion Extraction (OE) for Science and Technology Intelligence (STI) r
arXiv:2608.12679v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in discovery domains such as math and science. The usual approach is to present the problem to th
arXiv:2512.19799v2 Announce Type: replace Abstract: Advances in LLM reasoning and tool use have enabled agentic science, yet frontier theoretical and computational physics remains challenging because
arXiv:2608.13457v1 Announce Type: new Abstract: Generating crystals has recently attracted significant interest due to their broad applications in materials science. However, existing generative model
arXiv:2608.11844v1 Announce Type: new Abstract: Automated plant species identification from citizen-science imagery is an established, demanding fine-grained recognition problem: large taxonomic label
arXiv:2608.11362v1 Announce Type: cross Abstract: The computability of real numbers and functions using Turing Machines has been a central area of theoretical computer science since the mid-20th centu
arXiv:2608.10677v1 Announce Type: new Abstract: Professionals across medicine, engineering, finance, manufacturing, and the sciences often make consequential decisions from charts. Existing chart benc
arXiv:2608.10096v1 Announce Type: cross Abstract: Modern data science increasingly gives rise to hypothesis-testing problems that are not naturally formulated in terms of parameters within prespecifie
arXiv:2608.10881v1 Announce Type: new Abstract: The Traveling Salesperson Problem (TSP) is one of the best-known problems in computer science and arises in many engineering applications, such as smart
arXiv:2608.10234v1 Announce Type: cross Abstract: Operator learning is a rapidly advancing area of computational science. It is particularly well suited to problems where a partial differential equati
arXiv:2406.14373v3 Announce Type: replace Abstract: The emergence of Large Language Models (LLMs) and advancements in Artificial Intelligence (AI) offer an opportunity for computational social science
arXiv:2608.09748v1 Announce Type: cross Abstract: Decentralization as a concept in computer science has existed for over half a century. Despite its fundamental role across domains such as security, d
arXiv:2511.15941v2 Announce Type: replace-cross Abstract: Tabular data underpins decisions across science, industry, and public services. Despite rapid progress, advances in deep learning have not ful
arXiv:2608.07733v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) are widely used across domains such as natural sciences, social network analysis, chip design, and recommendation systems
arXiv:2511.17162v2 Announce Type: replace Abstract: The Belief-Desire-Intention (BDI) model is a cornerstone for representing rational agency in artificial intelligence and cognitive sciences. Yet, it
arXiv:2608.06860v1 Announce Type: cross Abstract: Hyperdimensional computing (HDC) is an approach from the cognitive science literature for solving information processing tasks using data represented
arXiv:2608.05630v1 Announce Type: new Abstract: Anaphors are expressions that refer to other expressions, called antecedents. The process of connecting the two is called resolution. Cognitive science
arXiv:2608.06137v1 Announce Type: new Abstract: Tabular data are ubiquitous in real-world applications and are crucial for data-driven prediction and decision-making across science, industry, finance,
arXiv:2608.04113v1 Announce Type: cross Abstract: Black-box optimization is a ubiquitous problem in science and engineering, often dealing with expensive objective functions with cheaper lower-fidelit
arXiv:2608.03600v1 Announce Type: new Abstract: Partial differential equations (PDEs) become actionable in science and engineering not as isolated formulae, but as executable workflows that connect mo
arXiv:2608.02775v1 Announce Type: new Abstract: Scientific discovery has advanced through successive transformations in the organization of knowledge. Observation and experimentation established the e
arXiv:2608.02505v1 Announce Type: cross Abstract: Can scientific abduction occur without continuous sensorimotor embodiment? Recent arguments in AI and philosophy of science hold that genuine hypothes
arXiv:2608.00542v1 Announce Type: new Abstract: Graphs model relational data throughout science and industry, from citation networks to product co-purchase graphs. Because the nodes of many such graph
arXiv:2608.00868v1 Announce Type: new Abstract: Many open educational resources are lacking in accessibility, especially in-depth image descriptions. In subjects like Science and Mathematics, however,
Hank Green, a popular YouTuber and science communicator, said he is stepping back from production amid intense criticism over his use of AI. Green described his AI usage as 'not healthy,' but stressed
arXiv:2608.02595v1 Announce Type: new Abstract: Language models are playing an increasingly important role in laboratory science, performing tasks such as experiment planning, execution, and post-hoc
arXiv:2608.02157v1 Announce Type: new Abstract: Raman spectroscopy enables non-destructive, label-free molecular characterization across materials science, biomedicine and process monitoring. Predicti
arXiv:2608.01378v1 Announce Type: new Abstract: Design campaigns in chemistry, materials science, and machine learning share a bottleneck: determining how good a candidate truly is requires an expensi
An internal version of our next major model produced 10 new results on long-standing open problems in mathematics and theoretical computer science, using roughly $2,000 worth of tokens at GPT-5.6 Sol
arXiv:2407.02025v5 Announce Type: replace-cross Abstract: Motivated by applications in chemistry and other sciences, we study the expressive power of message-passing neural networks for geometric grap
arXiv:2607.28553v1 Announce Type: new Abstract: Predicting the 3D structures of atomic systems is fundamental to advancing material science and drug discovery. While flow-matching models (, FlowDPO) h
arXiv:2607.28079v1 Announce Type: new Abstract: Chemical property prediction plays a critical role in accelerating scientific discovery in chemistry, materials science, and drug development. However,
arXiv:2301.01188v5 Announce Type: replace-cross Abstract: Deep R Programming is a comprehensive and in-depth introductory course on one of the most popular languages for data science. It equips ambiti
arXiv:2607.28347v1 Announce Type: new Abstract: LLMs are increasingly deployed as proxies for human study participants in social science experiments, yet the fidelity of this practice has rarely been
arXiv:2607.26587v1 Announce Type: cross Abstract: Automated research systems use experimental scores both to deliver artifacts and to decide which ideas to retain, transfer, and pursue. Yet one run sc
arXiv:2607.28304v1 Announce Type: new Abstract: Machine learning is transforming molecular sciences by accelerating property prediction, simulation, and the discovery of new molecules and materials. A
arXiv:2607.28498v1 Announce Type: cross Abstract: Scientific hypothesis generation for AI for Science typically involves Scientific Inspiration Retrieval (SIR) followed by hypothesis composition. Exis
arXiv:2506.10850v2 Announce Type: replace Abstract: Autonomous surface vessels (ASVs) are increasingly vital for marine science, offering robust platforms for underwater mapping and inspection. Accura
arXiv:2607.25681v1 Announce Type: new Abstract: Cognitive distortion amplifies negative emotions and contributes to mental health disorders. Cognitive Behavioral Therapy (CBT) is an effective way to a
arXiv:2607.24818v1 Announce Type: cross Abstract: Accurate prediction of crystal properties remains a key challenge in computational materials science. While graph neural networks (GNNs) such as CGCNN
arXiv:2607.23439v1 Announce Type: cross Abstract: Graphical models are ubiquitous in social and empirical science as they are intuitive and easy to use. These models belong to the broader class of Mar
arXiv:2607.23466v1 Announce Type: new Abstract: Parameterized and coupled partial differential equations (PDEs) are central to modeling phenomena in science and engineering, yet neural operator method
arXiv:2607.22683v1 Announce Type: new Abstract: With the unprecedented success of Language Models (LMs), the science of Prompt Engineering has evolved the powerful idea of Prompt Programming, where pr
arXiv:2607.23408v1 Announce Type: new Abstract: Expensive black-box optimization is ubiquitous in science and engineering, where function evaluations are costly and the evaluation budget is limited. T
arXiv:2607.22762v1 Announce Type: cross Abstract: Causal inference has become a central issue across various fields, including computer science, statistics, economics, education, healthcare, and medic
arXiv:2607.22684v1 Announce Type: cross Abstract: Artificial intelligence systems increasingly mediate how science is found and credited. We asked whether missing metadata prevents AI systems from cre
arXiv:2607.21702v1 Announce Type: new Abstract: Simulation-based inference (SBI) with machine learning is an increasingly important tool for solving inverse problems in science and engineering, includ
arXiv:2607.21233v1 Announce Type: new Abstract: Motivated by challenging modelling issues in the life sciences, we investigate the relationship between logic programming semantics and the eventual sta
arXiv:2607.21268v1 Announce Type: cross Abstract: In many social-science research tasks, such as economics, LLM-based agents must produce outputs for which no cheap, task-complete, machine-readable co
arXiv:2607.19498v1 Announce Type: cross Abstract: Gaussian process (GP) modeling is widely used in computational science and engineering. However, fitting a GP to high-dimensional inputs remains chall
arXiv:2509.15868v2 Announce Type: replace Abstract: Large-scale land cover maps generated using deep learning play a critical role across a wide range of Earth science applications. Open in-situ datas
arXiv:2607.19406v1 Announce Type: new Abstract: Structural elucidation from Nuclear Magnetic Resonance (NMR) data remains a fundamental bottleneck across chemistry, materials science, and biology. We
Earlier this month I hosted a fireside chat session at the AI Engineer World's Fair with Cat Wu and Thariq Shihipar from Anthropic's Claude Code team. We talked about Claude Code, Claude Tag, Fable, c
arXiv:2607.14072v1 Announce Type: new Abstract: Bioacoustic foundation models rely on large-scale citizen science platforms like Xeno-Canto for geographically and ecologically diverse data. Recent wor
arXiv:2607.11963v1 Announce Type: cross Abstract: The early detection of Chronic Kidney Disease using machine learning has attracted significant interest in healthcare-related computer science. Despit