Knowledge catalogue
arXiv:2603.25183v2 Announce Type: replace Abstract: Context-aware machine translation (MT) leverages document-level information, yet it does not consistently outperform sentence-level MT, as contextua
arXiv:2609.04749v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems have experienced rapid growth in recent years. Despite their promise, such systems remain fragile,
arXiv:2609.05364v1 Announce Type: cross Abstract: Machine-learning performance modeling is a uniquely hostile terrain for long-lived software: the assumptions baked into today's abstractions are inval
arXiv:2609.05363v1 Announce Type: new Abstract: Trade-up recommendation identifies higher-quality alternatives that preserve a customer's purchase intent while offering upgraded benefits. Large langua
arXiv:2602.09455v2 Announce Type: replace-cross Abstract: Affine Maximizer Auctions (AMAs), a generalized mechanism family from VCG, are widely used in automated mechanism design due to their inherent
arXiv:2609.04272v1 Announce Type: cross Abstract: This study examines the ability of large language models (LLMs) to predict the risk of weather-related forced outages in the distribution grid in a ze
arXiv:2607.09773v2 Announce Type: replace Abstract: Computer-use agents must solve long-horizon tasks through repeated interaction with partially observable, multimodal desktop environments. Although
arXiv:2609.04501v1 Announce Type: cross Abstract: Eye movement biometrics (EMB) is an emerging behavioral modality for user authentication, particularly in virtual- and augmented-reality systems, wher
arXiv:2609.04276v1 Announce Type: new Abstract: Vision-language models (VLMs), such as CLIP, have achieved strong performance across multimodal tasks by aligning visual and textual representations in
arXiv:2609.04277v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies have shown strong potential for general-purpose robotic manipulation, but they can still fail unpredictably duri
arXiv:2512.14675v2 Announce Type: replace Abstract: Contemporary reservoir computing relies heavily on globally Lipschitz, well-behaved activation functions, limiting applications in defense, disaster
arXiv:2609.04869v1 Announce Type: new Abstract: Computer-use agents can execute increasingly complex tasks in graphical interfaces, but their interaction experience is typically transient: procedural
arXiv:2502.01262v3 Announce Type: replace Abstract: Black-box adversarial attacks on semantic segmentation remain a challenging problem, particularly in the black-box transfer attack setting where per
arXiv:2609.04494v1 Announce Type: cross Abstract: We present Hakken, a domain-agnostic prediction and explanation system performing knowledge prediction, i.e., growing scientific knowledge by establis
arXiv:2609.04718v1 Announce Type: new Abstract: Structure-from-Motion (SfM) is a fundamental tool for sparse 3D reconstruction with broad impact in robotics and vision, supporting mapping, localizatio
arXiv:2609.05300v1 Announce Type: new Abstract: Safe robot navigation in dense crowds requires reasoning about pedestrian motion and how it may change in response to a robot. However, many learning-ba
arXiv:2609.05074v1 Announce Type: new Abstract: We propose an influence score to quantify the contribution of attention heads to classification decisions in Transformer-based models designed for promp
arXiv:2609.04800v1 Announce Type: new Abstract: Partially Relevant Video Retrieval (PRVR) aims to retrieve untrimmed videos that contain moments relevant to a text query. Since the target moment occup
arXiv:2609.04564v1 Announce Type: new Abstract: Self-driving laboratories (SDLs) combine automated experimentation with adaptive decision-making to accelerate scientific discovery. Their operation nev
OpenAI released GPT‑6 “Astra” — a model benchmarked for superior computer navigation, coding and complex math that can book DMV appointments and hunt apartments faster than an average user. The rollou
arXiv:2609.04942v1 Announce Type: new Abstract: Instruction-guided 3D editing is essential for interactive content creation, yet it faces a significant bottleneck: the severe scarcity of high-quality
arXiv:2609.05303v1 Announce Type: new Abstract: Hyperspectral and multispectral image fusion (HMIF) aims to reconstruct a high-resolution hyperspectral image (HR-HSI) by combining the fine spatial det
arXiv:2609.04511v1 Announce Type: new Abstract: Latent entity extraction (LEE) tackles the challenge of identifying implicit, contextually inferred entities within free text-an area where traditional
arXiv:2609.05334v1 Announce Type: cross Abstract: Chilli (Capsicum annuum) is one of India's most economically significant crops, yet its productivity is persistently threatened by diseases that are d
arXiv:2609.05327v1 Announce Type: new Abstract: Quantum circuits are central to implementing quantum algorithms on quantum devices, where quantum gates must be reversible. Many quantum algorithms rely
arXiv:2609.04840v1 Announce Type: new Abstract: Long-horizon predictive maintenance requires models to distinguish slowly evolving degradation from normal operating-regime variation over planning wind
arXiv:2603.14503v2 Announce Type: replace Abstract: Galaxy clusters are powerful probes of astrophysics and cosmology through gravitational lensing: the clusters' mass, dominated by 85% dark matter, d
arXiv:2609.05234v1 Announce Type: new Abstract: Continuous sliders are useful only when coefficient changes produce predictable image changes. Yet most diffusion sliders derive their axes from text or
arXiv:2609.04804v1 Announce Type: new Abstract: Synthetic medical time-series generation can alleviate data scarcity and support the development of reliable clinical prediction models. However, existi
arXiv:2609.04336v1 Announce Type: new Abstract: Medical visual question answering (Med-VQA) is often assumed to require medical fine-tuning, large models, or complex multi-agent pipelines. We revisit
arXiv:2603.18718v2 Announce Type: replace Abstract: Memory-augmented LLM agents maintain external memory banks to support long-horizon interaction, yet most existing systems treat construction, retrie
arXiv:2609.05075v1 Announce Type: new Abstract: General continual learning (GCL) aims to learn from evolving data streams without task identities, explicit boundaries, or repeated access to previous d
arXiv:2609.05206v1 Announce Type: new Abstract: Robotic hands vary widely in anatomical fidelity and mechanical complexity, and these structural choices influence the coordination of joint motions and
arXiv:2609.04250v1 Announce Type: cross Abstract: An avatar that holds a conversation should decide what to say and to move while saying it, yet these abilities live in separate model families: spoken
arXiv:2609.04574v1 Announce Type: cross Abstract: Multimodal Graph Neural Networks have become standard for recommendation by augmenting sparse interaction data with content features. Yet current arch
arXiv:2609.04864v1 Announce Type: new Abstract: Accurate station-level precipitation nowcasting is critical for agriculture, water resource management, and disaster prevention, which typically is form
arXiv:2609.04602v1 Announce Type: new Abstract: Fixed 3D Gaussian Splatting (3DGS) reconstructions provide realistic novel views but lack the traversability constraints, valid goals, and closed-loop p
arXiv:2609.05097v1 Announce Type: cross Abstract: AI-driven de novo molecular design offers a promising route to accelerate early-stage drug discovery by generating novel ligands directly within targe
arXiv:2609.05385v1 Announce Type: new Abstract: LLM decision components that can operate within agent workflows often produce action-relevant recommendations or judgements together with explanations.
arXiv:2609.04835v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used not only to retrieve information, but to answer questions, explain, teach, and support inquiry. In su
arXiv:2609.04921v1 Announce Type: cross Abstract: Diffusion probabilistic models can capture the multi-modal, interaction-rich distribution of joint future trajectories in driving scenes. We show that
arXiv:2602.06761v2 Announce Type: replace-cross Abstract: Fetal echocardiography is essential for detecting congenital heart disease (CHD), facilitating pregnancy management, optimized delivery planni
arXiv:2506.21185v3 Announce Type: replace Abstract: 3D semantic occupancy prediction is crucial for autonomous driving, providing a dense, semantically rich environmental representation. However, exis
arXiv:2609.04837v1 Announce Type: new Abstract: Single domain generalization (SDG) aims to learn a model from one labeled source domain that generalizes to unseen target domains. A common strategy is
arXiv:2609.04943v1 Announce Type: new Abstract: Recent benchmarks such as PowerGraph provide large collections of power-grid graphs for cascading-failure classification. Graph neural networks (GNNs) a
arXiv:2609.04715v1 Announce Type: new Abstract: Personalizing large language models (LLMs) is essential for delivering AI assistance that aligns with individual users' styles, intents, and preferences
arXiv:2609.05094v1 Announce Type: new Abstract: Electroencephalogram (EEG) visual decoding aims to recover visual semantics from non-invasive neural time-series signals, for which robust alignment bet
arXiv:2609.04793v1 Announce Type: new Abstract: Proteins perform diverse cellular functions, and even single amino-acid substitutions can alter stability, activity, or molecular interactions. Protein
arXiv:2609.04265v1 Announce Type: new Abstract: Existing post-hoc explainers for machine learning classifiers primarily focus on feature attribution, assigning importance scores to individual features
arXiv:2509.21889v3 Announce Type: replace Abstract: Existing evaluations of foundation models predominantly focus on output correctness, treating interaction as a static exchange of information. Howev
arXiv:2609.04271v1 Announce Type: new Abstract: Wi-Fi-based human activity recognition (HAR) has become an important part of integrated sensing and communications, paving the way for a range of contex
arXiv:2609.04878v1 Announce Type: cross Abstract: Fraudulent messages sent via Short Message Service (SMS) are increasingly obfuscated to evade cost-conscious classifiers in production systems. In Chi
arXiv:2609.04976v1 Announce Type: new Abstract: Personalization models generate new images guided by a few subject references, while style transfer methods aim to produce images aligned with a global
arXiv:2609.04415v1 Announce Type: cross Abstract: Learning rich medical concept representations is essential for EHR prediction. Text-attributed knowledge graphs (TKGs) provide a natural foundation by
arXiv:2609.05403v1 Announce Type: cross Abstract: Retail search systems serve diverse geographic regions with distinct query patterns, vocabularies, and product preferences, creating significant data
arXiv:2603.24131v2 Announce Type: replace-cross Abstract: Message passing is a core mechanism in Graph Neural Networks (GNNs), enabling the iterative update of node embeddings by aggregating informati
arXiv:2609.04689v1 Announce Type: cross Abstract: Early identification of Alzheimer's disease (AD) remains challenging because established assessment methods can be costly, resource-intensive, or unsu
arXiv:2609.04482v1 Announce Type: new Abstract: Safety alignment is usually posed as a topic-level question: is this subject harmful? Deployments ask a narrower one. A civics tutor and a public-sector
arXiv:2609.05141v1 Announce Type: new Abstract: Scientific papers require models to reason jointly over text, equations, figures, tables, code, and datasets while preserving the provenance of supporti
arXiv:2609.05263v1 Announce Type: cross Abstract: We investigate the best L_2 approximation of mixed Sobolev spaces by shallow neural networks with n neurons and general activation functions. We first