Knowledge catalogue
arXiv:2609.10518v1 Announce Type: new Abstract: fMRI foundation models increasingly aggregate heterogeneous data across brain states, cohorts, and acquisition settings, yet pretraining domains are com
Learn how to build an end-to-end RFI questionnaire workflow with Amazon Quick Automate. Read a multi-tab RFI workbook from Amazon S3, use natural-language prompts to extract and structure the question
arXiv:2609.10445v1 Announce Type: new Abstract: Reasoning language models have made substantial advances on a variety of complex tasks, yet their capabilities remain overwhelmingly English-centric: mo
arXiv:2609.09442v1 Announce Type: cross Abstract: In network traffic, legitimate behaviours and attack techniques evolve jointly - the phenomenon known as 'concept drift' [1]. Every detector is thereb
arXiv:2609.09705v1 Announce Type: new Abstract: Generalizable animal Re-Identification (ReID) aims to recognize individual animals across species with diverse morphologies and ecological contexts. Unl
arXiv:2609.09254v1 Announce Type: new Abstract: Field-programmable gate arrays (FPGAs) enable efficient neural-network inference, but most deployment flows either accelerate multiply-accumulate operat
arXiv:2609.10434v1 Announce Type: new Abstract: Self-supervised speech foundation models are now used in a wide array of downstream applications, including traditional speech recognition and as the ba
arXiv:2609.09439v1 Announce Type: cross Abstract: Ensuring the satisfaction of Signal Temporal Logic (STL) specifications under uncertainty is challenging, as reachability-based monitoring provides gu
arXiv:2609.10531v1 Announce Type: new Abstract: Image-to-3D models can generate visually compelling 3D assets from a single RGB image, but their geometry is often only loosely constrained by the avail
arXiv:2503.19599v3 Announce Type: replace-cross Abstract: While software requirements are often expressed in natural language, verifying the correctness of a program against such requirements is a har
arXiv:2411.10406v4 Announce Type: replace-cross Abstract: In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, sma
arXiv:2609.09626v1 Announce Type: new Abstract: Open-world object detection (OWOD) extends closed-set detection by requiring models to identify unknown objects and incrementally learn them once annota
arXiv:2609.05834v1 Announce Type: new Abstract: World models promise a general route to embodied intelligence: learn predictive dynamics once, then reason, plan, and act with them. Increasingly, the r
arXiv:2609.10490v1 Announce Type: new Abstract: This feature article provides an overview of the theoretical foundations for coVariance neural networks (VNNs), i.e., graph neural networks (GNNs) opera
Today, we're releasing a demo of WeWorm, the first zero-click worm to spread through WeChat calls across iOS and Android. [...] The victim does not need to answer the call, or interact with their phon
arXiv:2509.22404v2 Announce Type: replace Abstract: Anatomical understanding, which is the ability to identify, localize, or segment anatomical structures, is critical in medical image analysis; howev
arXiv:2609.07201v1 Announce Type: cross Abstract: Decompiled C often becomes recompilable only after repair, but recompilation alone does not establish test-observed behavior. A recompiled command-lin
arXiv:2609.05511v1 Announce Type: new Abstract: Web agents need to navigate visually rich, long-horizon interfaces that change across sites, yet most previous agents still learn each task in isolation
arXiv:2609.09595v1 Announce Type: new Abstract: Teacher-student systems, in which a teacher neural network generates training labels so that a student neural network can learn to implement the same fu
arXiv:2609.09974v1 Announce Type: new Abstract: Grapheme-to-phoneme conversion (G2P) refers to the task of converting a sequence of graphemes to a corresponding sequence of phonemes. While Filipino G2
arXiv:2512.21043v2 Announce Type: replace Abstract: Regulating grasping force to reduce slippage during dynamic object interaction remains a fundamental challenge in robotic manipulation, especially w
arXiv:2609.10287v1 Announce Type: new Abstract: Soft positional priors can help small Transformers learn retrieval circuits, but it is unclear whether the resulting circuits remain functional once the
arXiv:2609.09799v1 Announce Type: cross Abstract: Crystal structure prediction (CSP) is fundamental to computational materials discovery. Generative models including CDVAE, DiffCSP, FlowMM, and Crysta
TwelveLabs Marengo Embed 3.0 is now generally available as an embedding model in Amazon Bedrock Knowledge Bases, bringing fully managed natural language search to video, image, and audio content. This
arXiv:2609.09010v1 Announce Type: new Abstract: Three-dimensional femoral reconstruction from radiographs supports surgical planning, implant sizing, and post-operative follow-up, but remains ill-pose
arXiv:2609.05532v1 Announce Type: new Abstract: Background: Diagnosing head and neck cancer using PET/CT is clinically challenging and time-consuming due to the anatomical complexity of the region, mo
arXiv:2511.02821v2 Announce Type: replace-cross Abstract: We develop new accelerated first-order algorithms in the Frank-Wolfe (FW) family for minimizing smooth convex functions over compact convex se
arXiv:2507.08738v3 Announce Type: replace Abstract: Nonlinear vector autoregression (NVAR) and reservoir computing (RC) have shown promise in forecasting chaotic dynamical systems, such as the Lorenz-
arXiv:2609.06723v1 Announce Type: new Abstract: Meshes remain the most practical representation for geometry reasoning and integration into graphics pipelines, yet existing reconstruction methods stru
arXiv:2609.07046v1 Announce Type: new Abstract: AI has revolutionized various engineering domains, but its impact on semiconductor device design and defect discovery is still limited, due to limited d
arXiv:2609.08581v1 Announce Type: new Abstract: Formulaic alpha discovery is a pool-dependent symbolic search problem in which informative feedback is observed primarily when a complete expression is
arXiv:2510.09596v2 Announce Type: replace Abstract: Today's generative models thrive with large amounts of supervised data and informative reward functions characterizing the quality of the generation
arXiv:2609.07943v1 Announce Type: cross Abstract: There is significant uncertainty about whether abstractions like beliefs or desires usefully describe the behavior of large language models (LLMs). In
An embedded AI/BI dashboard can be securely shared with multiple viewers while ensuring that each viewer can see only their authorized rows. This protection is achieved through group‑based row‑level s
arXiv:2609.06837v1 Announce Type: cross Abstract: Embodied artificial intelligence has historically very much relied on visual perception, leading to a proliferation of multiple vision-centric world m
arXiv:2609.05575v1 Announce Type: cross Abstract: Understanding how concepts are encoded in the internal representations of machine learning models is a central problem in mechanistic interpretability
arXiv:2609.07183v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is sensitive to which problems a model trains on, yet existing selection criteria--difficulty fi
arXiv:2505.15215v4 Announce Type: replace-cross Abstract: Data fusion, the process of combining observational and experimental data, can enable the identification of causal effects that would otherwis
arXiv:2609.06807v1 Announce Type: new Abstract: In this work, we comprehensively evaluate three popular feature-extraction paradigms in AI-based neuroimaging modeling: (1) computation of anatomical su
arXiv:2609.06444v1 Announce Type: cross Abstract: An LLM judge evaluates outputs at scale. Experts should label only where it is least sure. Its natural escalation signal conflates two uncertainties:
arXiv:2609.08855v1 Announce Type: new Abstract: Machine learning emulators have become essential for accelerating expensive Earth-system simulations, but most existing approaches remain passive foreca
arXiv:2609.05972v1 Announce Type: new Abstract: We present an efficient and robust method for 3D geometric reconstruction that is based solely on the camera-independent linear relationships among a gi
arXiv:2609.07853v1 Announce Type: new Abstract: Semantic and goal-oriented communication is increasingly studied for 6G, but generalization beyond seen data remains a key weakness under tight rate bud
arXiv:2609.05846v1 Announce Type: cross Abstract: In function-on-function regression, the coefficient surface eta(s,t) may exhibit complex support structure---from localized patches to global patterns
arXiv:2609.05588v1 Announce Type: cross Abstract: World-action models (WAM) predict future states to guide robot actions, enabling learning from both action-free video and action-labeled interaction.
arXiv:2609.08153v1 Announce Type: cross Abstract: Generative diffusion models have emerged as a class of powerful techniques for various imaging applications, including but not limited to synthesis, r
arXiv:2609.08379v1 Announce Type: new Abstract: Accurate diagnostic and risk-prediction models are important for supporting clinical decision-making during infectious disease outbreaks. However, priva
arXiv:2603.23997v3 Announce Type: replace Abstract: Recovering high-fidelity 3D hand geometry from images is a critical task in computer vision, holding significant value for domains such as robotics,
arXiv:2609.08873v1 Announce Type: cross Abstract: Sparsity is a powerful structural resource in optimization and statistics. We develop frameworks for leveraging sparsity in sampling problems over the
Learn how Heurist built Heurist Finance, a conversational AI investment workbench, on Amazon Bedrock AgentCore. This customer story shows how AgentCore payments, Identity, Memory, Code Interpreter, an
arXiv:2504.21323v3 Announce Type: replace-cross Abstract: Knowledge distillation is widely used to transfer behavior from a large teacher model to a smaller student. It is often assumed to be safe whe
arXiv:2609.08380v1 Announce Type: cross Abstract: We study the stochastic first-order oracle complexity for constrained or regularized convex-concave min-max optimization and stochastic monotone varia
arXiv:2609.06079v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies leverage pretrained vision-language models (VLMs) to guide action generation for robot control. VLMs provide hie
arXiv:2609.08102v1 Announce Type: new Abstract: Machine learning surrogates based on neural operators have shown broad applicability in solving forward PDE problems. However, eigenvalue problems, in w
arXiv:2510.02532v2 Announce Type: replace-cross Abstract: Deep neural networks excel in high-dimensional problems, outperforming models such as kernel methods, which suffer from the curse of dimension
arXiv:2609.08851v1 Announce Type: new Abstract: Recent advancements in transformer length generalization theory enable us to reliably predict when a transformer can learn to solve a task. In particula
arXiv:1906.02590v2 Announce Type: replace-cross Abstract: This tutorial explains Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA) as two fundamental classification methods
arXiv:2609.05970v1 Announce Type: new Abstract: Empiric antibiotic therapy for suspected ESBL-producing Enterobacteriaceae must be selected 48-72 hours before culture results, forcing clinicians to ch
arXiv:2609.08958v1 Announce Type: new Abstract: Tensegrity robots offer lightweight, compliant mobility over challenging terrain but remain difficult to model and control due to complex contact-rich d
arXiv:2609.05820v1 Announce Type: new Abstract: We study adaptive routing of prompts to large language model (LLM) experts to maximize response quality in an online setting with limited feedback. We f