Knowledge catalogue
arXiv:2609.20245v1 Announce Type: new Abstract: Automated yoga analysis requires both accurate pose classification and interpretable feedback on pose execution. However, existing methods often rely on
arXiv:2609.20302v1 Announce Type: new Abstract: Multimodal gradient balancing methods modulate encoder gradients with a shared scalar per modality, implicitly assuming that corruption is uniform acros
arXiv:2609.19499v1 Announce Type: new Abstract: Test-time scaling can improve large language model reasoning by generating and combining multiple candidate responses. In sampling-based methods, the in
arXiv:2609.19150v1 Announce Type: new Abstract: Large language models (LLMs) encode rich stylistic structure in their hidden activations, but discovering which stylistic dimensions are salient for a g
arXiv:2607.18554v2 Announce Type: replace-cross Abstract: Learning local policies for continuous networked systems requires accounting for the effects of decisions beyond each agent's observation neig
arXiv:2609.20209v1 Announce Type: cross Abstract: Urban cellular activity forecasting requires jointly modeling heterogeneous spatiotemporal signals, including SMS usage, mobile network traffic, and c
arXiv:2609.20235v1 Announce Type: new Abstract: Indoor mobile robots require open-vocabulary scene understanding that grounds natural-language queries in a consistent 3D map. Many existing systems ult
arXiv:2603.29798v2 Announce Type: replace Abstract: Indoor 3D scenes are ultimately meant to be used: an embodied agent should be able to navigate, reach objects, and complete diverse activities. Yet
arXiv:2609.20419v1 Announce Type: cross Abstract: Graph foundation models (GFMs) aim to learn transferable representations across severely heterogeneous graph domains. However, severe domain shifts in
arXiv:2609.20398v1 Announce Type: new Abstract: Semantic parsing (SP)-based knowledge base question answering aims to answer natural language questions by generating executable logical forms (LFs) ove
arXiv:2609.19634v1 Announce Type: cross Abstract: This paper proposes a Retrieval-Augmented Generation (RAG) framework for scientific image quality assessment, designed to simultaneously address both
arXiv:2609.19644v1 Announce Type: new Abstract: Scientific discovery is defined by the ability to identify the boundaries of existing knowledge and venture into unexplored territory. The ultimate visi
arXiv:2602.03449v2 Announce Type: replace-cross Abstract: Score-based diffusion models are a recently developed framework for posterior sampling in Bayesian inverse problems, enabling high-quality rec
arXiv:2609.20807v1 Announce Type: new Abstract: Reinforcement learning (RL) of large language models is notoriously sensitive to small differences between training and inference engines, often referre
arXiv:2609.19483v1 Announce Type: new Abstract: Text-based person retrieval under a sim-to-real gap (synthetic training data, a real-image gallery) is usually tackled with costly fine-tuned cross-enco
arXiv:2609.19476v1 Announce Type: new Abstract: Generative models are increasingly central to many de novo discovery pipelines, in which designs are generated at scale and filtered through virtual scr
arXiv:2609.19444v1 Announce Type: new Abstract: Fine-grained evaluation of glomerular pathology must distinguish normal glomeruli from abnormalities such as global and segmental glomerulosclerosis, ob
arXiv:2609.19719v1 Announce Type: new Abstract: Automated visual analysis opens new avenues for behavior--based psychological measurement. Nevertheless, existing technological modules are typically sc
arXiv:2609.20451v1 Announce Type: new Abstract: Numerical site-response predictions often deviate from observations, yet correcting these discrepancies is difficult because records are limited in both
arXiv:2609.19592v1 Announce Type: new Abstract: This study developed and evaluated a deep-learning-based perception framework for selective robotic cotton picking. The dataset contained 1,008 annotate
arXiv:2609.20231v1 Announce Type: cross Abstract: Let (threshold(n)) be the largest integer (q) such that every loopless digraph on (n) vertices with at most (q) arcs is isomorphic to a spanning subdi
arXiv:2609.19656v1 Announce Type: cross Abstract: Information retrieval is increasingly important as LLM agents tackle complex tasks involving diverse information needs. Because retrieval relies on an
arXiv:2609.19480v1 Announce Type: new Abstract: The muscles that power insect flight fall into one of two categories: 1) synchronous muscles that contract under direct control from the nervous system,
arXiv:2609.19526v1 Announce Type: new Abstract: Coding agents can recursively modify their own implementations, forming a loop of self-improvement. While prior work shows this can boost performance on
arXiv:2609.19902v1 Announce Type: cross Abstract: We study an in-silico substrate in which every pixel of a two-channel cellular-automata grid carries a tiny neural network (an agent) that senses its
arXiv:2607.17986v2 Announce Type: replace-cross Abstract: Self-hosted AI agents maintain persistent memory, instructions, and configuration that influence their future behavior. If an agent is comprom
arXiv:2609.20768v1 Announce Type: cross Abstract: Generative agents are increasingly used to select and narrate video highlights, but they typically operate over unstructured or frame-level representa
arXiv:2609.19615v1 Announce Type: cross Abstract: Modern applications generate massive volumes of raw telemetry data, but translating those noisy, heterogeneous event streams into actionable business
arXiv:2609.20604v1 Announce Type: new Abstract: This paper presents a real-time semantic world modeling framework specialized for precision agriculture using autonomous robots. The framework combines
arXiv:2609.19330v1 Announce Type: new Abstract: Autonomous robots operating in partially observed environments must navigate safely while acquiring observations that improve future planning. Existing
arXiv:2609.20475v1 Announce Type: new Abstract: Open-vocabulary scene understanding is fundamental for robotics, laying the groundwork for spatial reasoning and object manipulation. While closed-vocab
arXiv:2609.20179v1 Announce Type: new Abstract: Human perception, action and decision making unfold in sequences, but computational predictors are often domain-specific. This study computes and tests
arXiv:2609.20086v1 Announce Type: new Abstract: Long-term multivariate time series plays a significant role in many application areas such as power systems, trading, etc. However, their accurate predi
arXiv:2510.10232v2 Announce Type: replace-cross Abstract: Recursive self-modification is increasingly central in AutoML, neural architecture search, and adaptive optimization, yet no existing framewor
arXiv:2609.20333v1 Announce Type: new Abstract: We study reconstruction in autoencoders that apply the same forward map before and after setting the observed coordinates to zero. For equal odd input a
arXiv:2609.19453v1 Announce Type: new Abstract: Antimicrobial resistance is expected to claim 10 million lives per year by 2050, and resource-limited regions are most affected. Raman spectroscopy is a
arXiv:2609.20700v1 Announce Type: new Abstract: Episodic test-time adaptation resets a frozen segmenter to source weights M_0 on each case and adapts for a fixed step count. A fixed horizon conflates
arXiv:2601.19406v2 Announce Type: replace-cross Abstract: Real-robot demonstrations are prohibitively expensive, while simulation data and real-world human demonstrations are both scalable but each le
arXiv:2609.19610v1 Announce Type: new Abstract: Understanding humans over long horizons requires agents to infer not only what people need in the moment, but also how routines form, why they repeat, a
arXiv:2609.20455v1 Announce Type: new Abstract: External skills provide domain procedures without parameter updates, but existing methods often edit skills directly from failed rollouts without struct
arXiv:2609.20648v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are a class of generalist robot policies that map camera images and language instructions directly to robot actions.
arXiv:2609.19533v1 Announce Type: new Abstract: Simultaneous localization and mapping (SLAM) is one of the services running on an autonomous robot. It is typically run to assist other tasks such as pl
arXiv:2609.19876v1 Announce Type: new Abstract: Floor-plan-based indoor visual localization enables infrastructure-free positioning, but most methods are developed and evaluated in small residential e
arXiv:2609.20166v1 Announce Type: new Abstract: Tiny transformers trained on fully-enumerable tasks occupy an unusual position in the study of grokking: every input can be evaluated, every generalizat
arXiv:2609.19359v1 Announce Type: new Abstract: Falls in older adults are often preceded by changes in mobility, balance, and postural transitions. This paper presents a wireless smart insole platform
arXiv:2609.20624v1 Announce Type: new Abstract: A robot sent to a named gas leak must preserve gas identity, estimate the source, and navigate to the resulting goal. We present SmellDiffusion, a simul
arXiv:2609.19815v1 Announce Type: new Abstract: We propose SnapPhysics, a training-free framework that reconstructs 3D objects and estimates their physical properties such as mass, friction, and cente
arXiv:2603.16128v3 Announce Type: replace Abstract: As autonomous LLM-based agents increasingly populate social platforms, understanding the dynamics of AI-agent communities becomes essential for both
arXiv:2609.19867v1 Announce Type: new Abstract: Joint learning across heterogeneous tasks is often treated as task coupling through feature sharing, distillation, or auxiliary supervision. However, in
arXiv:2609.20194v1 Announce Type: cross Abstract: Triangular membership functions (MFs) are widely used in fuzzy systems because of their interpretability, low parameterization complexity, and strong
arXiv:2609.19705v1 Announce Type: cross Abstract: Autonomous large language model (LLM) agents are moving rapidly into high-stakes domains, yet existing agentic-AI security studies remain largely doma
arXiv:2609.20519v1 Announce Type: new Abstract: As coding agents move from supervised code completion to unattended, around-the-clock exploration, their work expands from isolated predictions into lon
arXiv:2609.20091v1 Announce Type: new Abstract: The Antibandwidth and Cyclic Antibandwidth problems are NP-hard graph labeling problems that aim to maximize the minimum (cyclic) distance between label
arXiv:2609.20443v1 Announce Type: new Abstract: Robots searching for a target from a natural-language description must determine not only where to search, but also which observed candidate is the desi
arXiv:2609.20159v1 Announce Type: cross Abstract: We introduce a matrix generalization of the cone of Harvey and Lawson and prove that it is an exact special Lagrangian manifold. We further show that
arXiv:2609.20818v1 Announce Type: new Abstract: A splash lives for a fraction of a second: sheets tear into ligaments and droplets, appearance is view-dependent and nearly textureless, and little pers
arXiv:2609.20701v1 Announce Type: cross Abstract: We study efficient algorithms for realizing the first-order oracle complexity of optimization of G-Lipschitz convex functions with respect to the ell_
arXiv:2609.19418v1 Announce Type: cross Abstract: In evidence-based policymaking, typically one experimental sample is observed, then a learned policy recommendation is implemented at scale. Policies
arXiv:2609.20791v1 Announce Type: new Abstract: Hierarchical planning frameworks combine skills from multiple robot control policies for long-horizon task execution, where determining when to terminat
arXiv:2609.19747v1 Announce Type: new Abstract: Light field (LF) reconstruction from limited and noisy focal stack (FS) measurements is a highly ill-posed inverse problem. Although the LF-to-FS imagin