Learnable composition for neural operators
arXiv:2609.03069v1 Announce Type: new Abstract: Neural operators are fast, differentiable surrogates for physical simulation, but their accuracy often degrades when domain geometry, size, or operating
Knowledge catalogue
arXiv:2609.03069v1 Announce Type: new Abstract: Neural operators are fast, differentiable surrogates for physical simulation, but their accuracy often degrades when domain geometry, size, or operating
arXiv:2609.03343v1 Announce Type: cross Abstract: This paper addresses infinite-dimensional Bayesian inference for inverse problem of partial differential equations with model parameters in infinite-d
arXiv:2609.04194v1 Announce Type: new Abstract: Reasoning traces from chain-of-thought models appear to offer a legible window into how a model arrives at its answer. A growing body of work treats the
arXiv:2602.15154v2 Announce Type: replace Abstract: Reliable video understanding requires high-quality video datasets that can provide both precise semantic labels and temporally consistent annotation
arXiv:2609.03940v1 Announce Type: cross Abstract: Most previous work on speech enhancement (SE) based on masked generative modeling relied on discrete token representations of audio signals, obtained
arXiv:2609.03201v1 Announce Type: new Abstract: Long-term LLM agents must preserve information across interactions while distinguishing repeated evidence, historical states, updates, and unresolved co
arXiv:2512.03070v2 Announce Type: replace-cross Abstract: The advent of the big data paradigm has transformed how industries manage and analyze information, ushering in an era of unprecedented data vo
arXiv:2609.02986v1 Announce Type: new Abstract: Hybrid architectures combining Full Attention (FA) and Linear Attention (LA) are increasingly prominent, yet their allocation remains heuristic. We seek
arXiv:2603.08383v2 Announce Type: replace Abstract: Long-horizon indoor mobile manipulation (MoMa) requires robots to execute extended navigation-manipulation sequences whose feasibility depends on st
arXiv:2609.03603v1 Announce Type: new Abstract: Species Distribution Modelling (SDM) is essential for understanding how environmental conditions shape biodiversity, particularly for destructive pests
arXiv:2609.03694v1 Announce Type: new Abstract: Implicit neural representations (INRs) can model continuous 3D shapes with a shared coordinate decoder and per-instance latent codes. At test time, auto
arXiv:2609.03569v1 Announce Type: new Abstract: Head-mounted displays (HMDs) fundamentally limit emotion recognition in virtual reality (VR): by occluding the upper face, they render conventional imag
arXiv:2609.03919v1 Announce Type: new Abstract: We present OctWorld, a video diffusion framework with persistent 3D memory for generating explorable, world-consistent, and high-fidelity visual scenes.
arXiv:2511.17133v4 Announce Type: replace Abstract: Traditional in-camera colorimetric mapping relies on correlated color temperature (CCT)-based interpolation between pre-calibrated transforms optimi
arXiv:2609.03604v1 Announce Type: cross Abstract: Deep neural networks deployed in the wild must be both efficient and adaptable, requiring model compression and test-time adaptation (TTA). While both
arXiv:2609.04190v1 Announce Type: cross Abstract: Video editing spans diverse editing paradigms, yet achieving high-quality instruction-guided and subject-guided editing within a single unified framew
arXiv:2604.02881v2 Announce Type: replace-cross Abstract: Weight-space model merging combines independently fine-tuned checkpoints without access to the original training data. While merging has shown
arXiv:2609.03972v1 Announce Type: new Abstract: Label removal occurs frequently in classification systems with evolving taxonomies, where categories must be dynamically updated or eliminated. To accom
arXiv:2609.02896v1 Announce Type: new Abstract: Medical relation extraction (MRE) is commonly known for extracting entities and their relations jointly from a medical text, which has attracted conside
arXiv:2609.03655v1 Announce Type: new Abstract: Vision Foundation Models (VFMs) provide transferable patch representations for few-shot industrial anomaly detection, but their attention computation is
arXiv:2609.03341v1 Announce Type: new Abstract: We present PointGT, a point-based 3D representation that enables simultaneous editing of object geometry and appearance. Existing reconstruction and vie
arXiv:2609.03036v1 Announce Type: cross Abstract: Compliance screening of blockchain addresses is, in practice, a lookup against sanctions registries plus clustering heuristics; it fails on unlabelled
arXiv:2609.03453v1 Announce Type: new Abstract: Preprocessing-based defenses are the standard first-line response to adversarial attacks on edge vision systems, requiring no retraining, no architectur
arXiv:2609.03446v1 Announce Type: new Abstract: The continuous emergence of high-quality video deepfakes requires detectors that continually adapt to new forgery patterns, yet existing approaches, whi
arXiv:2609.03216v1 Announce Type: new Abstract: Vision Transformers (ViTs) typically process every image using a fixed input resolution and model width, even though many images can be classified with
In controlled offline evaluations, HydraFusion’s selective coding workflows matched or exceeded the evaluated Opus 5 baseline while reducing estimated workflow cost. Now available as a research previe
arXiv:2609.03762v1 Announce Type: new Abstract: The computation of the Bures-Wasserstein (BW) barycenter of an ensemble of positive definite matrices arises throughout machine learning, optimal transp
arXiv:2609.02894v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a prevailing paradigm for enhancing Large Language Models (LLMs) with non-parametric knowledge. Vanilla
arXiv:2609.03149v1 Announce Type: cross Abstract: Analog in-memory computing (AIMC) speeds up neural-network inference by doing the arithmetic directly inside a memory array, instead of shuttling weig
arXiv:2609.03430v1 Announce Type: new Abstract: Large language models achieve superior performance on tasks that require extended reasoning, but long chains of thought make the KV cache a severe memor
arXiv:2609.03956v1 Announce Type: cross Abstract: Medical image inpainting has the potential to improve automated brain MRI analysis by reconstructing healthy tissue within pathological regions. We in
arXiv:2609.03175v1 Announce Type: new Abstract: Multi-segment soft robotic arms can continuously reconfigure their body shapes for safe interaction, but tip control alone is insufficient for constrain
arXiv:2609.03379v1 Announce Type: new Abstract: Repeating a small block of middle layers increases a language model's effective inference depth without adding parameters or generating extra tokens, an
arXiv:2609.03643v1 Announce Type: cross Abstract: Let LsubseteqSigma^* and fix a morphism h:Sigma^*o M into a finite monoid. We study exact factorization and canonical presentation in the relative syn
arXiv:2511.18464v2 Announce Type: replace-cross Abstract: We study the problem of selecting the best heterogeneous treatment effect (HTE) estimator from a collection of candidates in settings where th
arXiv:2609.03626v1 Announce Type: cross Abstract: Rigorous results show that feedforward neural networks can overcome the curse of dimensionality in the numerical approximation of high-dimensional par
arXiv:2609.03265v1 Announce Type: new Abstract: Existing graph-clustering methods typically improve clustering performance by optimizing model parameters and node representations. Effective means of f
arXiv:2609.03235v1 Announce Type: new Abstract: Large language models (LLMs) face severe memory bottlenecks in long-context inference due to the linearly growing size of key-value (KV) caches. Existin
arXiv:2511.10866v2 Announce Type: replace-cross Abstract: This paper proposes a Short-Window Sliding Learning framework for real-time violence detection in CCTV footages. Unlike conventional long-vide
arXiv:2609.03377v1 Announce Type: new Abstract: Proteins are fundamental to biological processes, with their function determined by the complex interplay between the amino acid sequence and the three-
arXiv:2609.02941v1 Announce Type: cross Abstract: Speech emotion recognition (SER) faces two fundamental challenges: scarcity of labeled data and inter-speaker variability, both of which hinder genera
arXiv:2510.01984v4 Announce Type: replace Abstract: Quadruped mammals coordinate sagittal spinal bending with axial extension and compression during dynamic locomotion. Yet most robotic quadrupeds use
arXiv:2609.03401v1 Announce Type: cross Abstract: We first prove spectral convergence of the random feature method (RFM) for multidimensional targets in Sobolev, Gevrey, ultra-analytic, and bandlimite
arXiv:2609.03376v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has made dense retrieval over large document collections a standard building block. Organizations increasingly ou
arXiv:2609.03639v1 Announce Type: new Abstract: Training-free, camera-controlled novel view synthesis from a single image using pre-trained video diffusion models often becomes unstable under large ca
arXiv:2609.03447v1 Announce Type: new Abstract: Large-scale 3D surface reconstruction from aerial imagery is fundamental to geospatial mapping and urban modeling. Recent advances in 3D Gaussian Splatt
arXiv:2609.02963v1 Announce Type: cross Abstract: Lead optimization in structure-based drug design aims to improve target binding while avoiding unintended interactions with off-target pockets. Howeve
arXiv:2609.03382v1 Announce Type: cross Abstract: Predicting storm surge induced by landfalling tropical cyclones is crucial for flood mitigation and coastal risk management. Traditionally, physics-ba
arXiv:2609.03697v1 Announce Type: cross Abstract: In the natural sciences, symmetries and cause-effect relationships are ubiquitous. Yet for complex machine-learning tasks, like world-modeling in rein
arXiv:2609.04203v1 Announce Type: new Abstract: We introduce S^3T (Self-Supervised Self-Distillation over Time), which, to the best of our knowledge, is the first fully self-contained framework for co
arXiv:2609.03302v1 Announce Type: new Abstract: We present a unified computational approach to tensor-based morphometry in detecting the brain surface shape differences between two clinical groups bas
arXiv:2609.03622v1 Announce Type: cross Abstract: Test-time adaptation (TTA) offers a promising direction for improving speech enhancement models under mismatched acoustic conditions, without requirin
arXiv:2609.03585v1 Announce Type: new Abstract: Thermal infrared imaging offers reliable perception in darkness and adverse weather, but thermal datasets remain scarce, motivating extensive work on tr
arXiv:2609.03231v1 Announce Type: new Abstract: The ambition of the 2025 PNPL competition (Landau et al., 2025) was to launch a multi-year curriculum for non-invasive speech decoding. Designed to prog
arXiv:2609.04009v1 Announce Type: cross Abstract: Noisy annotations pose a significant challenge for supervised deep learning, as neural networks rely on large-scale, high-quality labeled data whose c
arXiv:2609.04005v1 Announce Type: new Abstract: We present an alternative characterization of the occupancy measure of reinforcement learning, obtained by embedding the planning criterion into the dyn
arXiv:2609.03090v1 Announce Type: new Abstract: Continuous chain-of-thought models compress reasoning into latent tokens. Matrix-valued variants, which route each latent token through a d x d matrix b
arXiv:2609.04046v1 Announce Type: cross Abstract: What can a single layer of self-attention compute? We study head complexity: the minimum number of attention heads required to compute a function in a
arXiv:2609.03829v1 Announce Type: cross Abstract: Few-shot fine-grained image classification (FSFGIC) aims to classify similar images with limited labeled examples. This work highlights the critical y
arXiv:2609.03633v1 Announce Type: cross Abstract: Chain-of-thought (CoT) reasoning improves large reasoning models (LRMs) on complex tasks but often produces long, redundant traces. Recent training-fr