Knowledge catalogue
arXiv:2609.27854v1 Announce Type: cross Abstract: Multi-source remote sensing image classification has attracted increasing attention due to the complementary spectral, structural, and geometric infor
arXiv:2609.28006v1 Announce Type: new Abstract: Decoder-only Transformer language models cache keys and values (KV) to reuse past computation during generation. Sharing KV across layers saves storage
arXiv:2609.27008v1 Announce Type: cross Abstract: We study the long-time behavior of Wasserstein gradient flows for interaction energies [ mathsf E[mu] = frac12iint_{Mimes M}K(x,y),mathrm dmu(x),mathr
arXiv:2609.27621v1 Announce Type: new Abstract: Physical modeling and inverse design require computation that can continue from reusable state. We introduce SHRAV, an architecture-independent computat
arXiv:2609.26820v1 Announce Type: cross Abstract: Physiological time series such as electrocardiograms (ECG) and electroencephalograms (EEG) exhibit complex temporal structure, substantial acquisition
arXiv:2606.13295v3 Announce Type: replace-cross Abstract: In the era of Explainable Artificial Intelligence, there is a renewed focus on single trees for their ease of interpretation. This paper intro
arXiv:2609.27980v1 Announce Type: new Abstract: Pruning large pre-trained transformer-based ASR models such as OpenAI's Whisper has seen great adoption, as pruning the decoder led to significant end-t
arXiv:2505.05491v2 Announce Type: replace-cross Abstract: Traffic sign detection is a challenging visual signal processing task for advanced driver assistance, where small objects, scale variation, an
arXiv:2609.28013v1 Announce Type: cross Abstract: Machine-learned interatomic potentials (MLIPs) for solid-liquid interfaces in advanced materials applications, e.g., electrochemistry, catalysis and c
arXiv:2609.27290v1 Announce Type: new Abstract: Short-horizon forecasts of atmospheric temperature are needed to support climate-aware digital-twin systems, but such forecasts must be produced where t
arXiv:2609.26854v1 Announce Type: cross Abstract: Sound Scene Generation is about the automatic synthesis of artificial sound scenes. We introduce SsgCaps, a publicly available dataset of human-engine
arXiv:2410.11113v4 Announce Type: replace-cross Abstract: This paper develops theory for deep neural network (DNN) estimators under dependent data. To provide theory applicable to a variety of DNN-bas
arXiv:2609.27238v1 Announce Type: new Abstract: Oriented ship detection in very high resolution (VHR) remote sensing imagery remains challenging due to elongated hull geometry and dense target distrib
arXiv:2609.28470v1 Announce Type: new Abstract: Artificial intelligence offers an unprecedented opportunity to augment human capabilities, yet progress at the frontier has focused primarily on advanci
arXiv:2609.27131v1 Announce Type: new Abstract: Single-image super-resolution of Sun's photospheric magnetograms enables consistent analysis across heterogeneous space-based instruments and supports l
arXiv:2409.13568v3 Announce Type: replace Abstract: Accurate delineation of agricultural field boundaries is essential for effective crop monitoring and resource management. However, competing methodo
arXiv:2609.27558v1 Announce Type: new Abstract: Studying syntactic patterns in naturally occurring language requires a large parsed corpus, but manual annotation is costly and difficult to scale. Thai
arXiv:2606.19329v2 Announce Type: replace-cross Abstract: We present a framework to cross-match sources from the Chandra Source Catalog (CSC v2.1) with optical sources from Gaia Data Release 3. Unlike
arXiv:2609.26811v1 Announce Type: new Abstract: Local learning trains each layer with its own auxiliary loss and no global backward pass, which makes layer updates structurally parallel. Two problems
arXiv:2609.27070v1 Announce Type: cross Abstract: Modern robot imitation learning increasingly relies on generative policies based on diffusion or flow-matching models, which generate actions by trans
arXiv:2609.27158v1 Announce Type: cross Abstract: To make claims about representations that generalize beyond a particular trained model, we need to specify when two representations should count as eq
arXiv:2609.28466v1 Announce Type: new Abstract: Advances in generative models have improved video fidelity, enabling long-horizon generation, interactive world modeling, and evolving visual environmen
arXiv:2609.27765v1 Announce Type: cross Abstract: In safe hypothesis testing with test supermartingales, Ville's inequality provides anytime-valid type-I error guarantees for every significance level
arXiv:2609.26978v1 Announce Type: cross Abstract: We study online inverse linear optimization with a fixed unknown linear utility: in each round, an environment presents a compact action set, the lear
arXiv:2609.27564v1 Announce Type: cross Abstract: The brain does not rely on a single type of neuron to perform all kinds of tasks; instead, it designs different neurons for different tasks. The conce
arXiv:2609.27868v1 Announce Type: cross Abstract: Octree-based 3D Gaussian Splatting organizes anchors into multi-level hierarchies for level-of-detail rendering, but features at different levels are
arXiv:2609.26990v1 Announce Type: cross Abstract: Natural Visibility Graph (NVG)-based representations provide a promising approach for capturing structural patterns in sequential network traffic. How
arXiv:2609.27675v1 Announce Type: new Abstract: Understanding articulated objects is fundamental for robotic interaction, requiring accurate rigid-part discovery and the recovery of their kinematic re
arXiv:2609.27037v1 Announce Type: new Abstract: Wake word detection is a critical component of virtual assistants, serving as the gateway to seamless user interactions. This paper introduces a novel w
arXiv:2609.26959v1 Announce Type: new Abstract: Solar photovoltaic (PV) forecasting in regions affected by load shedding is challenging because reliable historical observations are scarce. This study
arXiv:2609.28199v1 Announce Type: new Abstract: Long physiological recordings contain many routine measurements, while predictive information is often concentrated in rare events, sustained burden, an
arXiv:2609.27766v1 Announce Type: cross Abstract: In safe hypothesis testing with test supermartingals, Ville's inequality provides anytime-valid type-I error guarantees for every significance level a
arXiv:2609.27915v1 Announce Type: new Abstract: Despite remarkable advancements in multimodal large language models (MLLMs), their fine-grained visual understanding is constrained by a primary relianc
arXiv:2406.17699v3 Announce Type: replace-cross Abstract: Assume that we would like to estimate the expected value of a function F with respect to an intractable density pi, which is specified up to s
arXiv:2601.22524v2 Announce Type: replace Abstract: Graph generation aims to sample discrete node and edge attributes while satisfying coupled structural constraints. Diffusion models for graphs often
arXiv:2609.27219v1 Announce Type: new Abstract: Aerial radiation surveys achieve higher sensitivity when the radiation detector is held close to the ground. Detector sensitivity falls off roughly with
arXiv:2609.27948v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) demonstrate strong capabilities, they continue to suffer from a critical limitation: insufficient fine-grained visua
arXiv:2609.27088v1 Announce Type: new Abstract: Elongate multi-legged robots use coordinated body waves and distributed legs to move through cluttered terrestrial environments. However, as housing act
arXiv:2609.27865v1 Announce Type: cross Abstract: Sharing a deep encoder does not, by itself, fix the central confound of task-comparison scores. We show that cross-evaluated heads on a frozen shared
arXiv:2609.27954v1 Announce Type: new Abstract: A scalar recalibration map fitted for an LLM judge on one task can fail when the task distribution changes, but the source-target accuracy gap is often
arXiv:2609.26976v1 Announce Type: new Abstract: Learned context planning selects evidence atoms before an answer model reasons over them. We test whether this learned selection improves long-context m
arXiv:2609.27396v1 Announce Type: new Abstract: DSpark-style parallel drafters have made speculative decoding highly effective, yet their draft phase remains serialized on the critical path of every r
arXiv:2609.27033v1 Announce Type: cross Abstract: Reward fine-tuning aims to update a pre-trained flow-based generative model to improve the downstream reward of its generated samples. Existing method
arXiv:2609.28342v1 Announce Type: new Abstract: Removing an object from a real image requires more than synthesizing plausible content within a mask: the method must suppress residual object features,
arXiv:2609.25470v1 Announce Type: new Abstract: Bioinspired feedback controls for pursuit, tracking, and collective motion are often expressed in terms of the relative configuration between interactin
arXiv:2609.22956v1 Announce Type: new Abstract: Parkinson's disease alters gait and bilateral coordination, but machine-learning performance also depends on how continuous gait signals are represented
arXiv:2609.25012v1 Announce Type: new Abstract: Diachronic word embeddings have become the modern standard for tracking semantic change, yet they have been largely validated on modern, high-resource,
arXiv:2609.25614v1 Announce Type: new Abstract: This article presents a bimanual teleoperation pipeline and conceptual design of a deployable four-finger payload for intra-vehicular free-flyers. Futur
arXiv:2609.25471v1 Announce Type: new Abstract: Semi-supervised federated learning (SSFL) trains models on clients' unlabeled data using a teacher to generate pseudo-labels, with a small labeled seed
arXiv:2609.25639v1 Announce Type: new Abstract: Hip exoskeletons provide an important hardware basis for lower-limb rehabilitation and locomotor assistance. Laboratory rehabilitation assessment and sy
arXiv:2609.26539v1 Announce Type: new Abstract: Large language models (LLMs) have increasingly been used to investigate how children acquire syntax at an early stage of development. This is notably th
arXiv:2609.26218v1 Announce Type: cross Abstract: Structural graph analysis of the academic publishing network captures the topological relationships between entities but does not see the content of w
arXiv:2609.26679v1 Announce Type: new Abstract: In grokking an early fit to the training data separates from a much later improvement in generalization. During this delay, training can move from a fix
arXiv:2609.22695v1 Announce Type: new Abstract: The term 'linear representation hypothesis' (LRH) has appeared across diverse subfields of artificial intelligence, neuroscience, and cognitive science.
arXiv:2609.26237v1 Announce Type: cross Abstract: We present the ABAI submission to COLIEE 2026 Task 1, case law retrieval, together with a controlled study of why it underperformed. The task suppress
arXiv:2508.05229v2 Announce Type: replace-cross Abstract: EEG based multi-dimension emotion recognition has attracted substantial research interest in affective computing. However, the high dimensiona
arXiv:2609.22512v1 Announce Type: new Abstract: Consensus among LLM judges is often taken as strong evidence that a decision is correct. This assumes that judges make their errors independently. In pr
arXiv:2609.25725v1 Announce Type: new Abstract: Agricultural robotics is advancing rapidly, yet progress remains constrained by limited field access, lack of control over field conditions, geographic
arXiv:2609.25088v1 Announce Type: cross Abstract: Survival prediction for glioblastoma multiforme (GBM) demands models that are both accurate and interpretable, yet existing approaches treat these obj
arXiv:2609.22207v1 Announce Type: cross Abstract: High-rate neural telemetry requires an implant-towearable link whose circuit partition, waveform mapping, packet processing, and failure semantics are