Knowledge catalogue
arXiv:2609.34692v1 Announce Type: new Abstract: The reliable prediction of passenger train delays is a critical component of railway management. While contemporary research frequently attempts to maxi
arXiv:2609.32908v1 Announce Type: new Abstract: Neural theorem provers must both propose tactics and decide which valid successor states to explore. We study whether one-step Lean transitions provide
arXiv:2609.32652v1 Announce Type: cross Abstract: We study when geometry-induced soft state abstractions admit accurate finite-dimensional linear dynamics. Each state is represented by simplex-valued
Michael Shepard / Bloomberg: President Trump signs an executive order requiring federal government agencies to refer to AI as “Super Intelligence” or “SI” in all official communications — President Do
arXiv:2609.32354v1 Announce Type: new Abstract: This abstract addresses the incorporation of human motion prediction into proactive and dynamic human-aware motion planning, with the goal of enabling s
arXiv:2609.32811v1 Announce Type: new Abstract: Accident anticipation aims to recognize anomalous driving cues before a crash while avoiding false alarms during normal driving. Existing approaches typ
arXiv:2609.34784v1 Announce Type: new Abstract: Constructing a smooth approximation of an unsigned distance field (UDF) from a raw point cloud is challenging because the input provides neither surface
Prompt engineering in Amazon Quick shapes how accurately its AI-powered features respond to your requests. Part 1 of a two-part series covers the foundational principles and reusable frameworks (speci
arXiv:2609.35698v1 Announce Type: new Abstract: We study adversarial imitation learning (AIL), in which an agent learns to imitate expert demonstrations by optimizing a policy against an adversarial r
arXiv:2509.23762v4 Announce Type: replace-cross Abstract: Spiking Neural Networks (SNNs) have recently received increasing attention in both computational neuroscience and artificial intelligence owin
arXiv:2609.34273v1 Announce Type: cross Abstract: The projection of queries and keys are central to the attention mechanism in Transformer architectures. While they are mathematically symmetric, they
arXiv:2609.33674v1 Announce Type: new Abstract: Graph neural networks (GNNs) are often called long-range because their architecture can connect distant nodes, but this does not show whether they use d
arXiv:2609.35200v1 Announce Type: cross Abstract: Memory-dependent manipulation requires robots to make decisions using information that is no longer available to their current sensors, such as recall
arXiv:2609.34567v1 Announce Type: new Abstract: This review examines the evolution of plant phenotyping from conventional manual trait measurement to high-throughput, robotic, and artificial intellige
arXiv:2609.35034v1 Announce Type: cross Abstract: Off-policy evaluation, which estimates evaluation policy performance from logged data, is key for recommender ranking policies. However, logged clicks
arXiv:2609.32389v1 Announce Type: new Abstract: Filmmakers and visual artists routinely need to compose multiple references, actors, locations, props, cultural elements, into a single coherent shot, b
arXiv:2609.34904v1 Announce Type: new Abstract: Graph neural networks (GNNs) need to exploit improved message passing without surrendering control over predictions already trusted in deployment. We in
arXiv:2609.32516v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) process large volumes of alerts daily. Alert triage prioritizes high-risk threats while reducing manual review of b
arXiv:2609.32888v1 Announce Type: new Abstract: Gradient-based data selection methods such as LESS score each candidate by the alignment between its gradient and a target validation gradient, and reco
arXiv:2609.35612v1 Announce Type: new Abstract: Remote sensing novel view synthesis under sparse observations remains challenging due to insufficient geometric constraints and limited cross-view super
arXiv:2609.34177v1 Announce Type: cross Abstract: When an agent reuses logged experience, a changed decision may reflect the recorded score, the action's name, or the record's position in storage. Sta
arXiv:2609.33892v1 Announce Type: new Abstract: This paper proposes a residual learning-based control framework for heterogeneous vehicle platoons subject to parametric uncertainty and external distur
arXiv:2609.34701v1 Announce Type: cross Abstract: Multi-agent systems (MAS) are increasingly used to automate enterprise workflows involving multiple specialized agents, external tools, and long-runni
arXiv:2609.31932v1 Announce Type: cross Abstract: Low-Earth-orbit (LEO) satellites are increasingly expected to perform onboard learning for applications such as disaster response and environmental mo
arXiv:2609.35593v1 Announce Type: new Abstract: 3D vision transformers such as VGGT predict camera poses and scene geometry from multi-view images in a single forward pass, but their global attention
arXiv:2609.32590v1 Announce Type: new Abstract: Work on memory for multimodal agents optimizes what is written, updated and retrieved. Between retrieval and the answer, however, is a stage that multim
arXiv:2609.33716v1 Announce Type: new Abstract: Diffusion-based unsupervised domain adaptation (UDA) improves cross-domain transfer by generating target-specific synthetic data for downstream adaptati
arXiv:2609.34652v1 Announce Type: new Abstract: Medical time series (MedTS) underpin many clinical classification tasks, yet existing methods usually represent them only as numerical sequences and und
arXiv:2609.34004v1 Announce Type: new Abstract: Equity-relevant news evolves through temporally dependent corporate events, making historical information useful only when event continuity, information
arXiv:2609.32250v1 Announce Type: new Abstract: Sign-language interpretation in public communication relies on qualified professional interpreters and can be difficult to scale, motivating robotic sig
arXiv:2609.34897v1 Announce Type: new Abstract: Whole slide image classification is a fundamental task in computational pathology, where patch representation quality directly affects downstream aggreg
arXiv:2609.31698v1 Announce Type: new Abstract: Most existing MEG and EEG (M/EEG) visual decoding methods align brain signals with a single global embedding extracted from a pretrained visual encoder,
arXiv:2609.34527v1 Announce Type: new Abstract: We introduce the first real-time reflection-aware Gaussian SLAM system for indoor scenes. The system features a reflection-aware TSDF-Gaussian hybrid re
arXiv:2609.35637v1 Announce Type: new Abstract: Multi-tumor segmentation is important for early cancer detection and allows radiologists to visualize, verify, and understand AI predictions. However, t
arXiv:2609.33126v1 Announce Type: new Abstract: Group-relative reinforcement learning (RL) relies on reward variation among sampled responses to estimate informative relative advantages. As language m
arXiv:2609.33641v1 Announce Type: cross Abstract: Several businesses apply maintenance, repair, and overhaul (MRO) principles to the life-cycle of their existing products. In cases like casted gas tur
arXiv:2609.34499v1 Announce Type: new Abstract: Graph neural networks (GNNs) excel at representation learning on Knowledge Graphs (KGs), achieving stateof-the-art performance on tasks like link predic
arXiv:2609.32746v1 Announce Type: cross Abstract: While symbolic regression (SR) has been successfully used in science to discover new equations, its use in financial valuation is hindered by several
arXiv:2602.05464v2 Announce Type: replace-cross Abstract: Conditional representation learning aims to extract criterion-specific features for customized tasks. Recent methods construct conditional sub
arXiv:2609.34479v1 Announce Type: new Abstract: Vision-language (VL) pretraining using paired chest X-ray (CXR) images and radiology reports has shown strong potential for medical image understanding.
arXiv:2609.32529v1 Announce Type: new Abstract: Open-prompt detectors allow users to specify targets with text, visual exemplars, or both. We argue that existing designs underuse the visual modality i
arXiv:2609.34538v1 Announce Type: new Abstract: Looped Transformers reuse a shared block across recurrent depths, making autoregressive decoding expensive because every generated token requires many s
arXiv:2606.19504v2 Announce Type: replace Abstract: Recent advancements in Resistive Force Theory (RFT) enable approximation of ground reaction forces for locomotion in sand without the computational
arXiv:2609.32847v1 Announce Type: cross Abstract: We propose sliced Orlicz-Wasserstein (SOW) distance which is a generalization of sliced Wasserstein (SW) distance. SOW replaces the L^p norm in SW wit
arXiv:2609.35161v1 Announce Type: new Abstract: We present an in-depth investigation of how a form of Bayesian reasoning about common causes can emerge as a cross-contextual generalization in small, t
arXiv:2609.31645v1 Announce Type: new Abstract: Automated incident management in large-scale microservice systems relies on learning robust representations from multimodal observability data, includin
arXiv:2609.33408v1 Announce Type: new Abstract: In Integrated Sensing and Communications (ISAC), radar sensing must operate under chirp subsampling with up to 90% missing data. An attention-based base
arXiv:2609.35758v1 Announce Type: cross Abstract: We present a representation-learning framework for composite adaptive tracking control under dynamically coupled disturbances. The framework connects
arXiv:2609.34502v1 Announce Type: new Abstract: We present SubjectAnchor, a Subject-Aware Memory-to-Video paradigm for multi-shot storytelling in which the current shot is generated by conditioning on
arXiv:2602.15040v2 Announce Type: replace-cross Abstract: Accurate global Subseasonal-to-Seasonal (S2S) climate forecasting is critical for disaster preparedness and resource management, yet it remain
arXiv:2609.33964v1 Announce Type: cross Abstract: Directional multi-transmitter localization from sparse received-power observations is difficult because the receiver observes only the source-unresolv
arXiv:2609.34074v1 Announce Type: cross Abstract: In school choice, a lottery number is often used by the matching mechanism to break ties when there are more students who prefer the same school than
arXiv:2609.35392v1 Announce Type: new Abstract: Adam is the default optimizer for training modern deep neural networks, yet its adaptive behavior remains poorly understood due to the complex interacti
https://preview.redd.it/2fvmzd4f3ish1.png?width=952&format=png&auto=webp&s=d21e33fd26b46d2268a12219d8c0619666eb000e I thought something was off because browser_search was taking almost a minute for a
arXiv:2609.33291v1 Announce Type: cross Abstract: Many generative systems return multiple candidate responses and are evaluated according to the best one. Recent work shows that, when demonstrations a
arXiv:2609.34642v1 Announce Type: new Abstract: Schrodinger bridges provide an entropy-regularized framework and a principled solution for unpaired domain translation. In practice, a pretrained bridge
arXiv:2609.34297v1 Announce Type: new Abstract: Language-conditioned robot policies have made clear progress in multitask manipulation, but task-relevant local visual evidence usually stays hidden ins
arXiv:2609.33774v1 Announce Type: cross Abstract: Watermarking is a promising tool for establishing the provenance of AI-generated speech. While many neural audio watermarking methods rely on a separa
arXiv:2609.35481v1 Announce Type: cross Abstract: Dynamic routing creates severe load imbalance in large-scale expert-parallel Mixture-of-Experts (MoE) training, turning GPUs that host hot experts int
arXiv:2609.33915v1 Announce Type: new Abstract: Progress in machine learning cannot outpace our ability to verify it. With an explosion in papers today, every scientific claim rests initially on trust