Knowledge catalogue
arXiv:2604.06573v2 Announce Type: replace Abstract: A Grammatical Error Correction (GEC) system produces a sequence of edits to correct an erroneous sentence. The quality of these edits is typically e
arXiv:2605.03092v1 Announce Type: new Abstract: While sentiment analysis is the staple of financial NLP, capturing the nuances of 'why' behind that sentiment remains a challenge. There have been attem
arXiv:2605.03666v1 Announce Type: new Abstract: This work proposes a novel control and estimation approach for aerial manipulation of a cable-suspended load using Unmanned Aerial Vehicles (UAVs). Comm
arXiv:2605.03443v1 Announce Type: new Abstract: This paper benchmarks classical machine learning and deep learning approaches for three-class sentiment classification of Indonesian Spotify reviews. Us
arXiv:2512.16504v3 Announce Type: replace Abstract: The self-supervised pretraining paradigm has achieved great success in learning 3D action representations for skeleton-based action recognition usin
arXiv:2601.10931v2 Announce Type: replace Abstract: Tree canopy detection from aerial imagery is an important task for environmental monitoring, urban planning, and ecosystem analysis. Simulating real
arXiv:2605.03874v1 Announce Type: new Abstract: Classification of EEG signals using shallow Convolutional Neural Networks (CNNs) is a prevalent and successful approach across a variety of fields. Most
arXiv:2605.01307v1 Announce Type: cross Abstract: This paper investigates coordinated downlink transmission in a multi-base station (multi-BS) multi-reconfigurable intelligent surface (multi-RIS)-assi
arXiv:2510.24211v2 Announce Type: replace Abstract: Autoregressive (AR) modeling has recently emerged as a promising new paradigm in visual generation, but its practical adoption is severely constrain
arXiv:2603.03251v3 Announce Type: replace Abstract: Autoregressive decoding is bottlenecked by its sequential nature. Speculative decoding has become a standard way to accelerate inference by using a
arXiv:2605.02787v1 Announce Type: cross Abstract: SHACL (Shapes Constraint Language) expresses constraints on RDF data by means of so-called shapes. Its central service is validation: verifying whethe
arXiv:2605.03907v1 Announce Type: new Abstract: Large language models can be steered at inference time through prompting or activation interventions, but activation steering methods often underperform
arXiv:2605.03573v1 Announce Type: cross Abstract: In quantum machine learning (QML), classical data are often encoded as quantum pure states and processed directly as quantum representations, motivati
arXiv:2605.03429v1 Announce Type: cross Abstract: Artificial satellites and space debris increasingly contaminate astronomical images, affecting scientific surveys and producing large volumes of strea
arXiv:2605.01359v1 Announce Type: new Abstract: In this paper, we employ the Minimal Cognitive Grid (MCG), a framework created to evaluate the cognitive plausibility of artificial systems, to offer a
arXiv:2505.08262v2 Announce Type: replace Abstract: We study the classical binary classification problem for hypothesis spaces of Deep Neural Networks (DNNs) under Tsybakov's low-noise condition with
arXiv:2506.12818v3 Announce Type: replace Abstract: Bayesian optimization (BO) has traditionally solved black-box problems where function evaluation is expensive and, therefore, observations are few.
arXiv:2605.03780v1 Announce Type: cross Abstract: Transformers are effective at inferring the latent task from context via two inference modes: recognizing a task seen during training, and adapting to
arXiv:2605.03712v1 Announce Type: cross Abstract: Training-free conditional diffusion provides a flexible alternative to task-specific conditional model training, but existing samplers often allocate
arXiv:2509.10577v3 Announce Type: replace-cross Abstract: We study a basic question about cryptographic watermarking for generative models: how reliable can a watermark remain when an adversary is all
arXiv:2605.03936v1 Announce Type: new Abstract: Conceptual analysis -- proposing definitions and refining them through counterexamples -- is central to philosophical methodology. We study whether lang
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Inexpensive seafloor-hopping submersibles could stoke deep-sea
arXiv:2508.15524v3 Announce Type: replace Abstract: We present the first large-scale computational study of political delegitimization discourse (PDD), defined as symbolic attacks on the normative val
There are only two honest metrics when it comes to benchmarking intelligence: novelty and efficiency. You don't need intelligence to solve a known problem (only memory). And you don't need intelligenc
arXiv:2605.01418v1 Announce Type: new Abstract: Time-series generative models often lack control over temporal granularity, forcing users to accept whatever granularity the model produces. To enable t
arXiv:2605.01134v1 Announce Type: new Abstract: The dominant noun-based modeling paradigm has fundamentally constrained AI development, precluding any adequate representation of the future as an open
arXiv:2603.25169v2 Announce Type: replace Abstract: LLM performance is highly sensitive to prompt design, yet whether automatic prompt optimization can replace expert prompt engineering in linguistic
arXiv:2510.09511v2 Announce Type: replace-cross Abstract: Variable stiffness is a key capability in biological and robotic systems, enabling adaptive interaction across tasks and environments. Mechani
arXiv:2605.03348v1 Announce Type: new Abstract: We propose S3 (Specialization, Selection, Sparsification), a framework that rethinks multimodal learning through a structural perspective. Instead of en
arXiv:2605.02901v1 Announce Type: cross Abstract: This work aims to establish an end-to-end system for tracking of physical 3D objects for virtual reality (VR) applications. We focus on training appli
arXiv:2605.03953v1 Announce Type: cross Abstract: Several recent Transformer architectures expose later layers to representations computed in the earliest layers, motivated by the observation that low
arXiv:2605.03405v1 Announce Type: new Abstract: Attacking semantic segmentation models is significantly harder than image classification models because an attacker must flip thousands of pixel predict
arXiv:2605.01999v1 Announce Type: new Abstract: Classifying brain tumors using magnetic resonance imaging (MRI) is crucial for early diagnosis and treatment; however, tumor heterogeneity and a dearth
arXiv:2605.03379v1 Announce Type: cross Abstract: Repeated sampling is a standard way to spend test-time compute, but its benefit is controlled by the latent distribution of correctness across example
arXiv:2601.14505v2 Announce Type: replace-cross Abstract: In the network security domain, due to practical issues -- including imbalanced data and heterogeneous legitimate network traffic -- adversari
arXiv:2605.04044v1 Announce Type: new Abstract: Visual correspondence across image-to-image (2D-2D), image-to-point cloud (2D-3D), and point cloud-to-point cloud (3D-3D) geometric matching forms the f
arXiv:2605.03716v1 Announce Type: new Abstract: Multimodal visual object tracking can be divided into to several kinds of tasks (e.g. RGB and RGB+X tracking), based on the input modality. Existing met
arXiv:2605.02591v1 Announce Type: new Abstract: The efficacy of deep neural networks is heavily reliant on the design of non-linear activation functions, yet existing approaches often struggle to bala
arXiv:2605.00861v1 Announce Type: cross Abstract: This study investigates voice mapping as an evaluation framework for text-to-speech (TTS) synthesis quality. The study analyzes six TTS models, includ
arXiv:2605.03609v1 Announce Type: cross Abstract: Large language models often display heterogeneous moral preferences across settings. We study inference-time steering toward a desired ethical framewo
Wiki-Builder, a tool for creating LLM-powered wikis, was featured on Hacker News' front page, announced by DAIR.AI. The post indicates upcoming updates and improvements to make wiki creation more acce
arXiv:2605.00856v1 Announce Type: cross Abstract: Accurate and continuous estimation of cognitive workload is fundamental to creating adaptive human-machine systems. However, designing architectures t
arXiv:2512.01163v2 Announce Type: replace Abstract: Thermal analysis is increasingly critical in modern integrated circuits, where non-uniform power dissipation and high transistor densities can cause
Every few centuries, changes in how information moves reshape how societies govern themselves. The printing press spread vernacular literacy, helping give rise to the Reformation and, eventually, repr
arXiv:2507.04441v4 Announce Type: replace-cross Abstract: Conformal prediction (CP) produces prediction regions with finite-sample, distribution free coverage guarantees, but its interpretation as a q
arXiv:2605.00881v1 Announce Type: cross Abstract: Speckle noise severely limits the quality of images acquired from coherent imaging systems such as Synthetic Aperture Radar (SAR) and medical ultrasou
arXiv:2605.01066v1 Announce Type: new Abstract: R2 score is the standard metric for evaluating regression tasks, offering a normalized magnitude-agnostic measure of accuracy that captures variance. Ho
arXiv:2605.01381v1 Announce Type: new Abstract: Understanding how neural models represent human-interpretable concepts is challenging. Prior work has explored linear concept subspaces from diverse per
arXiv:2605.00858v1 Announce Type: cross Abstract: Owing to the recent advancements in wearable devices for health care, the importance of BP estimation without cuffs increases. Cuff technologies are i
arXiv:2605.02300v1 Announce Type: new Abstract: Applying concepts related to zero-shot meta-learning and pre-training of foundation models, we develop a meta reinforcement learning approach (denoted M
arXiv:2605.02035v1 Announce Type: new Abstract: Ambiguity resolution is a key challenge in multimodal machine translation (MMT), where models must genuinely leverage visual input to map an ambiguous e
arXiv:2605.02350v1 Announce Type: new Abstract: We study the complexity of smoothed agnostic learning of halfspaces on {pm 1}^n under the uniform distribution in the model of itet{KM25} where each inp
arXiv:2605.02507v1 Announce Type: new Abstract: Accurate prediction of Remaining Useful Life (RUL) in aero-engines is vital for predictive maintenance, improved operational reliability, and reduced li
arXiv:2601.10915v2 Announce Type: replace-cross Abstract: In the emerging paradigm of edge learning, neural networks (NNs) are partitioned across distributed edge devices that collaboratively perform
arXiv:2605.00923v1 Announce Type: cross Abstract: Accurate synthesis of computed tomography (CT) images from magnetic resonance imaging (MRI) is clinically valuable for cranial applications such as at
arXiv:2603.29895v2 Announce Type: replace-cross Abstract: We present a new theory of categorization based on an information-theoretic rational analysis. To evaluate this theory, we investigate how wel
arXiv:2605.00926v1 Announce Type: new Abstract: The Receiver Operating Characteristic (ROC) curve of a binary classifier has often been utilized to measure the performance of the classifier. The area
arXiv:2605.02838v1 Announce Type: cross Abstract: Retraction-free approaches offer attractive low-cost alternatives to Riemannian methods on the Stiefel manifold, but they are often first-order, which
arXiv:2605.01775v1 Announce Type: cross Abstract: We consider the problem of two-sample testing in a semi-supervised setting with abundant unlabeled covariate data. Standard two-sample tests neglect c
arXiv:2605.01170v1 Announce Type: cross Abstract: Reliable real-time 3D shape sensing is essential for robust control and interpretation of deformable systems during motion. Existing vision-based appr