Knowledge catalogue
arXiv:2609.20313v1 Announce Type: new Abstract: Point-of-Interest (POI) recommendation is a core task in location-based services, yet most existing methods assume a fixed user population and POI catal
arXiv:2609.19799v1 Announce Type: cross Abstract: LLM-driven evolutionary search finds programs by launching seeds and iterating each one. Papers report a single budget setting, usually one seed run f
arXiv:2609.19946v1 Announce Type: new Abstract: A geometrically valid placement can still be difficult to execute because the selected grasp changes the required end-effector pose, collision geometry,
arXiv:2609.19858v1 Announce Type: new Abstract: The problem of multiobjective optimization under uncertainties is often approached by taking the expectation of each objective. In this work, we propose
arXiv:2609.20217v1 Announce Type: new Abstract: Short-term traffic forecasting supports real-time monitoring and control of road networks, and graph attention networks (GAT) are the standard means of
arXiv:2606.15157v2 Announce Type: replace-cross Abstract: KV cache eviction methods typically use a single retention-rule family throughout a model, making eviction-method identity a model-level desig
arXiv:2609.19152v1 Announce Type: new Abstract: Misinformation detection tools often rely on binary true and false classifications or models trained on historical examples, limiting their usefulness w
arXiv:2609.20817v1 Announce Type: cross Abstract: Modeling articulated objects from sparse monocular views is challenging because each observation reveals only partial geometry and motion evidence. Mo
arXiv:2609.19475v1 Announce Type: new Abstract: Diffusion-based Vision-Language-Action (VLA) models achieve strong performance in embodied tasks, but their iterative sampling imposes heavy computation
arXiv:2609.20138v1 Announce Type: new Abstract: This work proposes a physics-enhanced machine learning approach for the system identification of Linear Time-Varying (LTV) systems under time-varying op
arXiv:2609.19383v1 Announce Type: new Abstract: Counterfactual (CF) explanations identify changes that alter an input's classification. While existing methods produce realistic and low-cost CFs, they
arXiv:2609.19549v1 Announce Type: cross Abstract: Communication is made possible by common ground---the unspoken knowledge that people share and presuppose of one another, whether that be online or of
arXiv:2609.20769v1 Announce Type: new Abstract: Flow matching has emerged as the state-of-the-art generative model and has been used for plug-and-play (PnP) priors to solve inverse problems in computa
arXiv:2609.19504v1 Announce Type: cross Abstract: As model-generated content is increasingly consumed by other model instances in automated workflows, a practically important question arises: can a mo
arXiv:2609.20207v1 Announce Type: new Abstract: Large language models produce prompt-dependent probabilities over words, whereas scientific systems require uncertainty over meaningful states that can
arXiv:2609.20535v1 Announce Type: new Abstract: Deep learning predictive maintenance models suffer from poor transferability across machines and operating conditions, especially when labelled data are
From @WSJopinion: The Hugging Face hack wasn’t what it was cracked up to be. Forget the “hive mind” of AI agents “going rogue.” They did what humans programmed them to do, writes Brian Gross. https://
arXiv:2609.19596v1 Announce Type: new Abstract: Full-duplex speech models listen and speak at once, promising always-on assistants. Yet they must also decide when they should speak. Human listeners sp
arXiv:2609.20673v1 Announce Type: new Abstract: To operate effectively in human environments, robots must identify articulated objects, segment their movable and interactive parts, and estimate their
arXiv:2609.19315v1 Announce Type: cross Abstract: Large language models (LLMs) provide a flexible interface for long-horizon robot planning, but generated plans often fail to respect embodiment constr
arXiv:2609.19887v1 Announce Type: new Abstract: Pronouns, adverbs and other functional words (such as they, her, somewhere, there) are often used in language to replace concrete nouns or phrases, when
arXiv:2609.20358v1 Announce Type: new Abstract: Characterizing the physical properties of clay and cementitious materials matters across many fields, from materials science to geological waste disposa
arXiv:2609.20087v1 Announce Type: new Abstract: Effective manipulation across diverse objects is critical for applications ranging from agricultural harvesting to laboratory and domestic automation. W
arXiv:2609.20481v1 Announce Type: cross Abstract: Conferences, journals, funders, schools, and universities are struggling with a surge of potentially AI-generated submissions from ostensibly human au
arXiv:2609.19907v1 Announce Type: new Abstract: Gaussian Splatting (GS) excels at novel-view synthesis but encodes baked-in radiance, tightly entangling illumination with geometry and preventing seaml
arXiv:2603.00087v2 Announce Type: replace-cross Abstract: We revisit High-Resolution Range Profile (HRRP) classification with aspect-angle conditioning. While prior work often assumes that aspect-angl
Hi everyone, The NeurIPS results aren’t out yet, but I’m expecting my paper to be rejected, so I’m considering submitting it to a journal instead. My scores were 2/3/3 (3/4/4). I feel like I would pro
arXiv:2609.20814v1 Announce Type: cross Abstract: Pretraining a neural PDE surrogate can reduce the amount of new CFD data needed when geometry or modeled physics changes. However, it remains unclear
arXiv:2609.20311v1 Announce Type: cross Abstract: We read the geometry of semantic neighbourhood graphs as modal logic and give that reading a statistical form, in order to make precise the structural
arXiv:2609.20309v1 Announce Type: new Abstract: Spatially heterogeneous partial differential equations (PDEs) exhibit location-dependent dynamics arising from variations in geometry and physical coeff
arXiv:2609.20396v1 Announce Type: new Abstract: Robots operating in cluttered environments must often manipulate objects whose locations are only partially observable. A central challenge is deciding
arXiv:2609.19693v1 Announce Type: new Abstract: The rapid increase of deepfakes has raised significant concerns due to their spread on social media. Traditional multi-face forgery detectors crop and v
arXiv:2609.19650v1 Announce Type: new Abstract: Sequential sentence classification (SSC) is an essential task for structuring scientific publications, and extending SSC research to languages other tha
arXiv:2609.20297v1 Announce Type: new Abstract: A recogniser trained on one person rarely transfers to the next, and useful performance usually demands a fresh round of labelled calibration from the e
arXiv:2609.19775v1 Announce Type: new Abstract: Published medical case reports serve as a crucial medical information carrier, documenting discoveries in rare diseases, diagnostic methods, and innovat
arXiv:2410.23969v3 Announce Type: replace-cross Abstract: We consider the problem of testing and learning from data in the presence of resource constraints, such as limited memory or weak data access,
arXiv:2609.20151v1 Announce Type: new Abstract: Objectives: Quantitative assessment of infarct hypodensity on non-contrast computed tomography (NCCT), including net water uptake (NWU), requires manual
arXiv:2609.20752v1 Announce Type: cross Abstract: Falsification searches for counterexamples to formal specifications in cyber-physical systems (CPS). With specifications written in Signal Temporal Lo
arXiv:2604.25639v2 Announce Type: replace-cross Abstract: This paper is accepted and in press for AI and Ethics. This paper includes the supplementary data file at the end of the manuscript. This stud
arXiv:2510.21736v2 Announce Type: replace-cross Abstract: This study introduces a novel control framework for adaptive cruise control (ACC) in automated driving, leveraging neural networks and physics
arXiv:2609.19288v1 Announce Type: new Abstract: Learning in recurrent neural networks can fundamentally reshape their underlying dynamics, transforming initially chaotic activity into stable task-depe
arXiv:2609.20581v1 Announce Type: new Abstract: Discrete diffusion, including remasking and uniform-state samplers, generate a sequence by writing multiple token positions per step, drawing each from
arXiv:2609.19515v1 Announce Type: new Abstract: Verifier-based selection improves LLM performance by generating multiple candidate solutions and using a verifier to select the most promising one. Howe
arXiv:2609.19374v1 Announce Type: new Abstract: Small clinical tabular datasets require interpretable machine learning because deep learning is often impractical and ensemble models can be difficult t
arXiv:2609.20670v1 Announce Type: new Abstract: Robots that localize a radio transmitter need more than a point estimate: in cluttered rooms, one measurement is often consistent with several transmitt
arXiv:2609.19385v1 Announce Type: cross Abstract: Cardiovascular disease (CVD) remains the leading cause of death among women, yet cardiovascular risk assessment often relies on clinical variables tha
arXiv:2609.19683v1 Announce Type: cross Abstract: The deployment of Vision-Language Models (VLMs) on edge devices is severely bottlenecked by memory bandwidth, necessitating aggressive sub-8-bit quant
arXiv:2609.20181v1 Announce Type: new Abstract: Accurate skin lesion segmentation is crucial for reliable computer-aided dermatological diagnosis, yet existing convolutional and transformer-based mode
arXiv:2609.20650v1 Announce Type: new Abstract: Federated learning enables collaborative training without sharing patient-level data, but most studies remain simulations. Based on five requirements de
arXiv:2609.20327v1 Announce Type: cross Abstract: We study smooth strongly convex--strongly concave minimax optimization with general nonlinear coupling in the deterministic unconstrained setting. We
arXiv:2609.20160v1 Announce Type: new Abstract: Monitoring flying animals is important for understanding and protecting biodiversity, but nocturnal species such as bats are difficult to observe in the
arXiv:2609.19529v1 Announce Type: cross Abstract: Suppose we observe the first n points of a sequence of random variables having length n+1, and wish to estimate a functional of the unobserved final p
arXiv:2609.20523v1 Announce Type: cross Abstract: Quantum communication underpins secure information processing and scalable quantum networks. In particular, remote state preparation (RSP) enables eff
arXiv:2609.19302v1 Announce Type: new Abstract: Open datasets describing human behavior in environments shared with mobile robots remain limited, particularly for retail activities that combine locomo
arXiv:2609.19955v1 Announce Type: new Abstract: We study the problem of recovering the parameters of a multivariate Ornstein-Uhlenbeck (OU) process from steady-state observational and interventional d
arXiv:2609.19891v1 Announce Type: new Abstract: Gaussian Processes (GPs) are widely used as surrogates for black-box functions in sequential decision-making problems such as Bayesian optimization (BO)
arXiv:2609.20454v1 Announce Type: cross Abstract: Accurate optimization of a supervised spectral objective need not produce an accurate population subspace or a better predictive representation. We in
arXiv:2609.19230v1 Announce Type: new Abstract: Ultrasound is the most widely deployed imaging modality worldwide, yet clinical AI remains fragmented into narrow single-task models that fail when devi
arXiv:2609.20658v1 Announce Type: new Abstract: When does work done with AI still feel like ours? As AI becomes woven into everyday tasks, we must examine what happens to our sense of ownership and co
arXiv:2609.20634v1 Announce Type: new Abstract: Allen's interval algebra is a qualitative calculus for temporal relations, but its thirteen base relations are crisp predicates over exact interval boun