Knowledge catalogue
arXiv:2608.15601v1 Announce Type: new Abstract: Compositional Concept Generalization (CoCoGen), the ability to systematically recombine learned primitives in novel contexts, is a key challenge for mul
arXiv:2608.16168v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly use external memory systems to support personalization by drawing on long and evolving interaction hist
arXiv:2604.03491v2 Announce Type: replace-cross Abstract: This paper proposes a method for estimating a surface that contains a given set of points from noisy measurements. More precisely, by assuming
arXiv:2603.06187v2 Announce Type: replace-cross Abstract: We introduce the Random Quadratic Form (RQF): a stochastic differential equation which formally corresponds to the gradient flow of a random q
arXiv:2608.14638v1 Announce Type: new Abstract: In this paper we study autoencoders, a special class of deep neural nets (DNNs) whose performance can be characterized via their fixed points. This pers
arXiv:2608.14764v1 Announce Type: new Abstract: With the increasing integration of renewable energy sources, energy storage systems have become essential, making the accurate estimation of their State
arXiv:2608.16421v1 Announce Type: new Abstract: This paper presents an ontology-supported approach to tackle the complexity of the Robustness Validation (RV) process of automotive electrical/electroni
arXiv:2608.16473v1 Announce Type: new Abstract: Neural PDE training yields a finite checkpoint archive, yet its logged energy errors are inaccessible without the exact solution, while loss-based selec
arXiv:2608.15560v1 Announce Type: new Abstract: Human demonstrations offer a scalable data source for dexterous manipulation, but transferring them to robot actions remains challenging due to the embo
arXiv:2608.14994v1 Announce Type: new Abstract: Reconstructing a spatially and spectrally high-resolution hyperspectral image (HR-HSI) from a low-resolution HSI (LR-HSI) and a high-resolution RGB imag
arXiv:2608.15784v1 Announce Type: new Abstract: Soft piezoresistive strain sensors are one of the most common sensing solutions for wearable and soft robotic applications due to their flexibility and
arXiv:2608.15951v1 Announce Type: new Abstract: We study when a wearable stress system should surface a prediction rather than change it. In low-stakes reflection and summary settings, aggregate accur
arXiv:2608.15269v1 Announce Type: new Abstract: Long-horizon robot policies require compact access to recent observations and reusable experience without expanding the vision-language-action (VLA) con
arXiv:2608.16484v1 Announce Type: new Abstract: Remote-sensing systems usually describe urban content with detection boxes, semantic masks, or vector boundaries. Such outputs locate classes and suppor
arXiv:2412.18911v3 Announce Type: replace-cross Abstract: Diffusion Transformers (DiT) have become the dominant methods in image and video generation yet still suffer substantial computational costs.
arXiv:2608.16480v1 Announce Type: cross Abstract: We present RISE (Roadside Infrastructure Sequence Understanding and Evaluation), a framework spanning metric 3D tracking and structured vision-languag
arXiv:2608.15785v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables real-time novel-view synthesis but remains limited on GPUs at high resolutions. Through a stage-wise Roofline chara
arXiv:2608.15621v1 Announce Type: new Abstract: Human Activity Recognition (HAR) with self-administered wearables, such as at-home rehabilitation and exercise monitoring, often requires reattaching in
arXiv:2608.15787v1 Announce Type: cross Abstract: Two Mixture-of-Experts (MoE) forward passes can share every weight yet route the same token through different experts. This creates a possible blind s
arXiv:2608.15694v1 Announce Type: cross Abstract: Conditional image-to-image generators are single-shot: they map input features to an output in one forward pass and treat it as final, with no opportu
arXiv:2608.15429v1 Announce Type: new Abstract: Prior embedding models for sequential recommendation typically operate within a homogeneous action space, limiting their ability to capture cross-surfac
arXiv:2608.15652v1 Announce Type: new Abstract: The rapid proliferation of generative models raises the model attribution problem: given only an image, can we determine which model produced it? Existi
arXiv:2608.15863v1 Announce Type: cross Abstract: Operating household appliances requires long-horizon planning that is state-dependent and robust to disturbances, yet existing large models fall short
arXiv:2608.16251v1 Announce Type: new Abstract: Face recognition templates are compact identity representations, yet they also encode rich semantic information about facial appearance. Prior work has
arXiv:2608.15824v1 Announce Type: new Abstract: Adam retains a moving average of past squared gradients in its denominator, but the optimization cost of this memory is not well understood. We show tha
arXiv:2608.15962v1 Announce Type: new Abstract: Long-context reasoning remains computationally expensive for large language models due to the quadratic complexity of attention over text tokens. Visual
arXiv:2505.07372v3 Announce Type: replace-cross Abstract: This paper presents a novel methodology for enhancing Automated Program Repair (APR) through synthetic data generation utilizing Large Languag
arXiv:2608.15443v1 Announce Type: new Abstract: Parts of speech categorization is understood in the European linguistic tradition as crisp categorization, which is also reflected in corpus linguistics
arXiv:2308.11290v2 Announce Type: replace-cross Abstract: Understanding the dynamics of large quantum systems is hindered by the curse of dimensionality. Statistical learning offers new possibilities
arXiv:2608.16463v1 Announce Type: new Abstract: Sparse-view spectral computed tomography (CT) reconstructs energy-resolved attenuation volumes from limited projection views, requiring simultaneous han
arXiv:2608.14944v1 Announce Type: cross Abstract: Natural-language interfaces can lower the barrier to programming robots, but existing systems struggle when users request complex tasks. While large l
arXiv:2510.15911v3 Announce Type: replace-cross Abstract: The Sleeping Beauty problem is a problem of imperfect recall that has received considerable attention. One approach to solving the Sleeping Be
arXiv:2508.09105v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) and its Multimodal Retrieval-Augmented Generation (MRAG) significantly improve the knowledge coverage and conte
arXiv:2608.14936v1 Announce Type: new Abstract: Small proxy models are commonly used to identify data mixtures for larger-scale training. We ask whether their training trajectories reveal another tran
arXiv:2608.15295v1 Announce Type: new Abstract: Foundation segmentation models excel at generating high-quality, class-agnostic masks, but they struggle to associate these proposals with specific targ
arXiv:2608.16172v1 Announce Type: new Abstract: At every re-observation point in a hierarchical Vision-Language-Action (VLA) system, two interface decisions must be made: when to terminate the current
arXiv:2608.15632v1 Announce Type: cross Abstract: Neural representations have become a central tool for studying the internal mechanisms of modern AI models, yet their complex high-dimensional structu
arXiv:2608.16878v1 Announce Type: cross Abstract: For any convex body KsubsetR^{n} containing a unit ball, the spectral gap of Hit-and-Run is Omega(1/(n^2 C_{mathsf{PI}})), where C_{mathsf{PI}} is the
arXiv:2608.15548v1 Announce Type: cross Abstract: Machine unlearning (MU) aims to remove the influence of specific training data while preserving model utility. As the name suggests, MU can be viewed
arXiv:2608.15001v1 Announce Type: cross Abstract: We construct spinning conformal fields from neural networks and the embedding formalism, computing their two-, three- and four-point functions in exam
arXiv:2608.16863v1 Announce Type: new Abstract: Generating photorealistic novel views from unposed images requires both 3D geometric understanding and the ability to synthesize unseen content. A natur
arXiv:2608.16585v1 Announce Type: new Abstract: Video Diffusion Transformers (DiTs) spend most of their compute inside the Self-Attention operation, whose cost grows quadratically, O(n^2), with the nu
arXiv:2608.16224v1 Announce Type: cross Abstract: By leveraging large-scale pretraining, LLMs can interpret diverse temporal expressions and question formulations without task-specific training. Howev
arXiv:2608.16309v1 Announce Type: cross Abstract: Static pruning is widely used to accelerate sparse neural retrieval, yet existing studies each validate their conclusions within a single custom pipel
arXiv:2608.16791v1 Announce Type: cross Abstract: Model Inversion Attacks (MIAs) aim to reconstruct representative training samples of target identities from face recognition models, exposing critical
arXiv:2608.14648v1 Announce Type: cross Abstract: In this study, we revisit three widely used techniques in vector search and utilize them to optimize vector embedding indexing through clustering: dim
arXiv:2608.15224v1 Announce Type: new Abstract: Reliable post-hoc evaluation asks whether already generated text satisfies a target criterion after generation. In this paper we study a focused frozen-
arXiv:2608.15121v1 Announce Type: cross Abstract: Sufficient dimension reduction (SDR) seeks the minimal subspace of the predictors that captures the full conditional distribution of the response, whi
arXiv:2606.17215v2 Announce Type: replace Abstract: A certificate that removes outliers sees the data only through its low-degree moments, and an adversary exploits exactly this, hiding corruption whe
arXiv:2608.16380v1 Announce Type: cross Abstract: Monitoring war-induced damage to agricultural land in Ukraine is important for understanding threats to food security, environmental stability, and po
arXiv:2608.14953v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have opened opportunities to apply high-level code transformations to the field of code optimization, an
arXiv:2608.15968v1 Announce Type: new Abstract: Low-cost four-degree-of-freedom (DoF) arms are among the most accessible robotic platforms. But they are, in theory, underactuated for picking up in sit
arXiv:2608.14789v1 Announce Type: new Abstract: Large low-Earth-orbit (LEO) Earth-observation (EO) constellations offer frequent access to geographically dispersed ground targets, but emergency reques
arXiv:2608.15768v1 Announce Type: cross Abstract: Conformal prediction (CP) provides distribution-free coverage guarantees and has emerged as a principled tool for uncertainty quantification. In edge-
arXiv:2608.14759v1 Announce Type: cross Abstract: Whole Slide Image (WSI) analysis has been widely studied for cancer diagnosis. Conventionally, a gigapixel WSI is divided into small patches and proce
arXiv:2608.16861v1 Announce Type: cross Abstract: We initiate a polyhedral study of the graph multi-separator problem proposed by Irmai et al. (2024) as an alternative to the lifted multicut problem f
arXiv:2608.15215v1 Announce Type: cross Abstract: Token-level knowledge distillation (KD) matches two conditional distributions per position, yet the standard objectives compare them pointwise: a Kull
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arXiv:2608.15971v1 Announce Type: cross Abstract: Dual-encoder models such as CLIP score an image-caption pair by a single inner product of two independently computed unit vectors, and fail at binding
arXiv:2607.18237v2 Announce Type: replace Abstract: Human visual similarity judgments are context-dependent. For example, two images may be similar in shape but distinct in color. Existing perceptual