Knowledge catalogue
arXiv:2609.19853v1 Announce Type: cross Abstract: Between a screenplay and a film sits a planning problem that is spatial first: who stands where, and what a camera sees from where it stands. An image
arXiv:2609.20177v1 Announce Type: new Abstract: Forecasting corporate tax avoidance proxies from firm--year panel data is challenging because predictive signals are distributed across short firm histo
'People built the test, removed restraints, defined the objective, left a route open and decided not to stop what was happening. Calling the result 'rogue AI' does more than sensationalize it. It allo
arXiv:2609.19215v1 Announce Type: cross Abstract: Traditional codecs treat every region of a frame alike; a generative layer can instead degrade the regions a viewer attends to least and reconstruct t
arXiv:2311.08493v2 Announce Type: replace-cross Abstract: This research aims to investigate the classification accuracy of various state-of-the-art image classification models across different categor
arXiv:2609.19542v1 Announce Type: new Abstract: Open-vocabulary segmentation enables rich semantic perception for UAVs, but frame-wise predictions can remain temporally inconsistent across repeated ob
arXiv:2609.20296v1 Announce Type: new Abstract: A myoelectric interface needs calibration from the user before it will function. Earlier work has treated calibration as a quantity, but has not asked t
arXiv:2602.06577v2 Announce Type: replace-cross Abstract: Complex-valued neural networks (CVNNs) are rising in popularity for all kinds of applications. To safely use CVNNs in practice, analyzing thei
arXiv:2609.20623v1 Announce Type: new Abstract: Recent single-view feed-forward 3D Gaussian Splatting (3DGS) generation predicts a fixed number of Gaussians per camera ray, introducing severe spatial
arXiv:2609.19776v1 Announce Type: new Abstract: Estimating temporal soil-loss change is challenging when physically meaningful input factors are noisy or corrupted, particularly because substantial ch
arXiv:2609.19290v1 Announce Type: cross Abstract: Clinical decision-making for coronary intervention relies mainly on angiography and fractional flow reserve (FFR). However, angiography is two-dimensi
arXiv:2609.19782v1 Announce Type: cross Abstract: Figurative paintings are often approached as if they depict a single recoverable 3D scene: viewers infer depth and occlusion, and reconstruction pipel
arXiv:2609.20638v1 Announce Type: new Abstract: An assistant watching egocentric video should notice a mistake from past frames alone, before the next step begins, and keep working once the person rec
arXiv:2609.20732v1 Announce Type: new Abstract: Semantic cell annotation improves chunking interpretability for spreadsheets in LLM-driven RAG systems, aiding answer generation through enriched contex
arXiv:2609.20156v1 Announce Type: cross Abstract: Ubiquitous time series data across diverse domains enables critical applications in areas such as transportation systems and power grids. Recently, tr
arXiv:2609.20283v1 Announce Type: new Abstract: Modern segmenters often fail after the expensive computation has already been done: a useful mask is present among the model's query-conditioned candida
arXiv:2609.19279v1 Announce Type: new Abstract: Running artificial intelligence (AI) models directly on edge devices such as smartphones, wearables, and drones offers low latency, pervasive scalabilit
arXiv:2609.20507v1 Announce Type: new Abstract: Micro- and nano-plastic particles (MPs/NPs) are ubiquitous environmental contaminants whose increasing abundance and potential health impacts have creat
arXiv:2609.19236v1 Announce Type: new Abstract: Objective: Incomplete navigation of anatomy during ureteroscopic kidney stone surgeries can contribute to repeat interventions. While skilled surgeons h
arXiv:2609.20081v1 Announce Type: cross Abstract: SpeechLLMs have shown strong potential for emotion recognition, yet they read the predicted emotion off a generative decoder not suited for classifica
arXiv:2609.20594v1 Announce Type: new Abstract: Quantum long short-term memory (QLSTM) models extend recurrent sequence learning with variational quantum circuits, but their optimization behavior can
arXiv:2609.20633v1 Announce Type: new Abstract: Text-guided image editing must introduce the requested changes while preserving unrelated source content. Diffusion-based editors rely on spatial contro
arXiv:2609.20530v1 Announce Type: new Abstract: We present Relational BabyLM, a system submission to the BabyLM 2026 challenge that combines two cognitively motivated inductive biases in a single deco
arXiv:2609.19831v1 Announce Type: cross Abstract: In this reproducibility study, we investigate the transparency and scrutability of recommender systems enhanced by incorporating generated natural-lan
arXiv:2312.01020v3 Announce Type: replace Abstract: Stock prices forecasting has always been a challenging task. Although many research projects try to address the problem, few of them pay attention t
arXiv:2609.20489v1 Announce Type: cross Abstract: One hospital runs bloods and imaging at the same time. Another runs them one after the other, in either order, equally often. Knowing which actually h
arXiv:2609.19421v1 Announce Type: new Abstract: Gaussian Splatting has significantly improved the quality of novel view synthesis with explicit Gaussian representation. However, we observed that exist
arXiv:2609.19241v1 Announce Type: cross Abstract: Large language models fine-tuned for network intrusion detection emit single-point predictions without statistical validity guarantees. Conformal pred
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:2609.20209v1 Announce Type: cross Abstract: Urban cellular activity forecasting requires jointly modeling heterogeneous spatiotemporal signals, including SMS usage, mobile network traffic, and c
arXiv:2609.19634v1 Announce Type: cross Abstract: This paper proposes a Retrieval-Augmented Generation (RAG) framework for scientific image quality assessment, designed to simultaneously address both
arXiv:2609.19719v1 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:2609.20231v1 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:2609.19480v1 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:2609.20475v1 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:2609.20333v1 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:2609.20166v1 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:2609.20443v1 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:2609.20701v1 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:2609.19363v1 Announce Type: new Abstract: The query and key projections WQ,WK in attention are almost always trained by Euclidean optimizers with no constraint on their geometry. We constrain th
arXiv:2609.19940v1 Announce Type: cross Abstract: In previous papers, we began the study of sequence prediction algorithms adapted to stringological word complexity measures. In particular, we defined
arXiv:2609.20213v1 Announce Type: new Abstract: Dimensionality reduction is a well-known technique for improving space efficiency, typically applied uniformly across an entire dataset. This paper inve
arXiv:2505.03953v3 Announce Type: replace Abstract: When solving optimization problems under uncertainty with contextual data, utilizing machine learning to predict the uncertain parameters' values is
arXiv:2609.20577v1 Announce Type: cross Abstract: We study the Bayes-optimal spherical linear model as the ambient dimension and sample size grow proportionally, under a quantitative Marchenko--Pastur
arXiv:2609.20150v1 Announce Type: new Abstract: Conventional satellite remote sensing transmission follows a reconstruct-then-infer paradigm that optimizes pixel-level fidelity, creating an objective
arXiv:2609.19616v1 Announce Type: new Abstract: Complexity measured from generated code is failure-dependent: a difficult prompt can yield a short failing program and be assigned low output complexity
arXiv:2510.09022v2 Announce Type: replace Abstract: Recent Machine Learning (ML) approaches have shown increased performance on benchmarks at the cost of escalating compute demands. Hardware, algorith
arXiv:2609.20687v1 Announce Type: cross Abstract: We study first-order black-box convex optimization over an ell_p-ball for objectives Lipschitz in the ell_q-norm, solving in the affirmative the nonsm
arXiv:2609.19730v1 Announce Type: cross Abstract: Accurate estimation of left ventricular ejection fraction (EF) from echocardiography is central to cardiovascular care, and deep learning enables auto
In recent weeks, leaders of some of the biggest AI companies have warned that the very tech they are developing is dangerous. Last weekend, Anthropic CEO Dario Amodei argued that AI carries serious ri
arXiv:2609.19448v1 Announce Type: new Abstract: In both cognitive science and computer science, goals are conceptualized as cognitive states that flexibly combine with world knowledge to organize and
arXiv:2609.19770v1 Announce Type: new Abstract: All-atom structure predictors model diverse molecular interactions, but using their learned structural priors for binder design remains challenging. Her
arXiv:2609.20199v1 Announce Type: new Abstract: Cognitive workload reflects the mental effort required during task performance and is central to the design of adaptive human-machine systems. The use o
arXiv:2609.20465v1 Announce Type: new Abstract: We train neural networks on synthesized frames to approach the optimum Bayes estimator for dense emitter localization. The result justifies the future w