Knowledge catalogue
arXiv:2602.20376v2 Announce Type: replace-cross Abstract: We approach the Max-3-Cut problem through the lens of maximizing complex-valued quadratic forms and demonstrate that low-rank structure in the
arXiv:2604.22251v1 Announce Type: new Abstract: Variable impedance model predictive control (MPC) formulations that treat joint stiffness as an instantaneous decision variable operate on a feasible se
arXiv:2505.14234v2 Announce Type: replace-cross Abstract: Entropic measures like Shannon entropy (SE), its quantum mechanical analogue von Neumann entropy, and Kullback-Leibler divergence (KL) are key
arXiv:2604.22254v1 Announce Type: new Abstract: We address the problem of searching for an unknown number of stationary targets at unknown positions with a mobile agent. A probability hypothesis densi
arXiv:2604.22534v1 Announce Type: cross Abstract: Feature engineering for Electronic Health Records (EHR) is complicated by irregular observation intervals, variable measurement frequencies, and struc
arXiv:2508.15025v5 Announce Type: replace Abstract: We consider federated learning of linearly-parameterized nonlinear systems. We establish theoretical guarantees on the effectiveness of federated no
arXiv:2604.22494v1 Announce Type: cross Abstract: We introduce two federated learning frameworks for the classical SPDnet model operating on symmetric positive definite (SPD) matrices with Stiefel-con
arXiv:2604.21950v1 Announce Type: cross Abstract: Small language models (1-3B) are practical to run locally, but individually limited on harder code generation tasks. We ask whether composing them int
arXiv:2604.22328v1 Announce Type: cross Abstract: Driven by the transition towards a climate-neutral energy system, accurate energy time series forecasting is critical for planning and operation. Yet,
arXiv:2602.06974v2 Announce Type: replace-cross Abstract: Visual navigation for robotics is inspired by the human ability to navigate environments using visual cues and memory, eliminating the need fo
arXiv:2604.22334v1 Announce Type: new Abstract: Recent advances in pretraining 3D point cloud encoders (e.g., Point-BERT, Point-MAE) have produced powerful models, whose abilities are typically evalua
arXiv:2604.22166v1 Announce Type: new Abstract: While language models demonstrate sophisticated syntactic capabilities, the extent to which their internal mechanisms align with cross-constructional pr
arXiv:2604.22176v1 Announce Type: cross Abstract: Accurate mapping between Common Vulnerabilities and Exposures (CVE) and Common Weakness Enumeration (CWE) entries is critical for effective vulnerabil
arXiv:2604.22093v1 Announce Type: new Abstract: Reliable visual perception under low illumination remains a core challenge for autonomous robotic systems, where degraded image quality directly comprom
arXiv:2604.22339v1 Announce Type: new Abstract: Handling the dynamic environments is a significant research challenge in Visual Simultaneous Localization and Mapping (SLAM). Recent research combines 3
arXiv:2604.22586v1 Announce Type: new Abstract: We propose FlowAnchor, a training-free framework for stable and efficient inversion-free, flow-based video editing. Inversion-free editing methods have
arXiv:2505.14351v4 Announce Type: replace-cross Abstract: Tibetan is a low-resource language with minimal parallel speech corpora spanning its three major dialects-U-Tsang, Amdo, and Kham-limiting pro
arXiv:2604.21952v1 Announce Type: cross Abstract: This work presents a multi-layered methodology for efficiently accelerating multimodal foundation models (MFMs). It combines hardware and software co-
arXiv:2604.21982v1 Announce Type: new Abstract: Solar panels are increasingly deployed in cities on rooftops, walls, and urban infrastructure. Although the panel costs have fallen in recent years, the
arXiv:2604.22018v1 Announce Type: cross Abstract: Several brain foundation models (FM) have recently been proposed to predict brain disorders by modelling dynamic functional connectivity (FC). While t
arXiv:2604.22190v1 Announce Type: cross Abstract: CLIP-based person re-identification (ReID) methods aggregate spatial features into a single global exttt{[CLS]} token optimized for image-text alignme
arXiv:2604.22626v1 Announce Type: new Abstract: This study investigates the structural organisation of Dante's Divina Commedia through a symbolic representation based on vowel-consonant (V/C) encoding
arXiv:2601.11020v3 Announce Type: replace Abstract: Advances in mechanistic interpretability have identified special attention heads, known as retrieval heads, that are responsible for retrieving info
arXiv:2604.22416v1 Announce Type: cross Abstract: Latent variables pose a fundamental challenge to causal discovery and inference. Conventional local methods focus on direct neighbors but fail to prov
arXiv:2604.22601v1 Announce Type: cross Abstract: Large Language Models (LLMs) show promise in automated software engineering, yet their guarantee of correctness is frequently undermined by erroneous
arXiv:2604.22446v1 Announce Type: new Abstract: Individual agent capabilities have advanced rapidly through modular skills and tool integrations, yet multi-agent systems remain constrained by fixed te
arXiv:2602.21750v2 Announce Type: replace Abstract: Protein language models (PLMs) have become widely adopted as general-purpose models, demonstrating strong performance in protein engineering and de
arXiv:2604.22615v1 Announce Type: new Abstract: Embodied foundation models have achieved significant breakthroughs in robotic manipulation, yet they still depend heavily on large-scale robot demonstra
arXiv:2604.22724v1 Announce Type: new Abstract: Imitation learning is a well-established approach for machine-learning-based control. However, its applicability depends on having access to demonstrati
arXiv:2604.22084v1 Announce Type: new Abstract: Malware attacks have a significant negative impact on organizations of varied scales in the field of cybersecurity. Recently, malware researchers have i
arXiv:2604.22700v1 Announce Type: new Abstract: Understanding and predicting the progression of neurodegenerative diseases remains a major challenge in medical AI, with significant implications for ea
arXiv:2604.22160v1 Announce Type: cross Abstract: Human visual perception offers valuable insights for understanding computational principles of motion-based scene interpretation. Humans robustly dete
arXiv:2507.13706v2 Announce Type: replace Abstract: This paper introduces two quasi-metrics for performance assessment of multi-object tracking (MOT) algorithms. One quasi-metric is an extension of th
arXiv:2503.21435v3 Announce Type: replace Abstract: Recent advances in Vision-Language Models (VLMs) have shown promising capabilities in interpreting visualized graph data, offering a new perspective
arXiv:2604.22045v1 Announce Type: cross Abstract: Feature attribution methods explain the predictions of deep neural networks by assigning importance scores to individual input features. However, most
arXiv:2603.04855v3 Announce Type: replace Abstract: Student Personas (SPs) are emerging as infrastructure for educational LLMs, yet prior work often relies on ad-hoc prompting or hand-crafted profiles
arXiv:2601.10386v2 Announce Type: replace-cross Abstract: Accurate survival prediction in Non-Small Cell Lung Cancer (NSCLC) requires integrating clinical, radiological, and histopathological data. Mu
arXiv:2604.22388v1 Announce Type: new Abstract: Transrectal ultrasound (TRUS) imaging is a cost-effective and non-invasive modality widely used in the diagnosis of prostate cancer. The computer-aided
arXiv:2508.15919v3 Announce Type: replace-cross Abstract: Large language model (LLM) serving faces the dual challenge of meeting strict user-specific service-level objectives (SLOs) while minimizing c
arXiv:2604.22293v1 Announce Type: cross Abstract: Lookup-table (LUT) based neural networks can deliver ultra-low latency and excellent hardware efficiency on FPGAs by mapping arithmetic operations dir
arXiv:2604.22407v1 Announce Type: cross Abstract: Many continual-learning methods modify gradients upstream (e.g., projection, penalty rescaling, replay mixing) while treating Adam as a neutral backen
arXiv:2604.22482v1 Announce Type: new Abstract: While feed-forward 3D reconstruction models have advanced rapidly, they still exhibit degraded performance on panoramas due to spherical distortions. Mo
arXiv:2506.09520v2 Announce Type: replace-cross Abstract: Human planning is efficient--it frugally deploys limited cognitive resources to accomplish difficult tasks--and flexible--adapting to novel pr
arXiv:2604.22750v1 Announce Type: new Abstract: The wide adoption of AI agents in complex human workflows is driving rapid growth in LLM token consumption. When agents are deployed on tasks that requi
arXiv:2604.22422v1 Announce Type: cross Abstract: We consider the following fundamental problem: given a database D, Boolean conjunctive query (CQ) q, and fact f in D, decide whether f is relevant to
arXiv:2604.22193v1 Announce Type: new Abstract: Large language models (LLMs) often need to balance their internal parametric knowledge with external information, such as user beliefs and content from
arXiv:2511.18903v2 Announce Type: replace-cross Abstract: Due to the scarcity of high-quality data, large language models (LLMs) are often trained on mixtures of data with varying quality levels, even
arXiv:2604.22271v1 Announce Type: new Abstract: Large language models can detect their own errors and sometimes correct them without external feedback, but the underlying mechanisms remain unknown. We
arXiv:2604.22103v1 Announce Type: cross Abstract: Street-view perception models predict subjective attributes such as safety at scale, but remain correlational: they do not identify which localized vi
arXiv:2604.22679v1 Announce Type: cross Abstract: The increasing adoption of AI systems in hiring has raised concerns about algorithmic bias and accountability, prompting regulatory responses includin
arXiv:2502.03698v4 Announce Type: replace Abstract: Learning from demonstrations is a popular approach to train AI models; however, their vulnerability to adversarial attacks remains underexplored. We
arXiv:2604.22442v1 Announce Type: new Abstract: We introduce HubRouter, a pluggable module that replaces O(n^2) attention layers with O(nM) hub-mediated routing, where M =20 shows increasing seed sens
arXiv:2604.22506v1 Announce Type: new Abstract: Low-Resolution License Plate Recognition (LRLPR) remains a challenging problem in real-world surveillance scenarios, where long capture distances, compr
arXiv:2604.22631v1 Announce Type: new Abstract: Modern automatic speech recognition (ASR) systems have been observed to function better for certain speaker groups (SGs) than others, despite recent gai
arXiv:2510.27241v2 Announce Type: replace Abstract: Recent theoretical advancement of information density in natural language has brought the following question on desk: To what degree does natural la
arXiv:2604.22479v1 Announce Type: new Abstract: Driver drowsiness is a major cause of traffic accidents worldwide, posing a serious threat to public safety. Vision-based driver monitoring systems ofte
arXiv:2604.22062v1 Announce Type: new Abstract: There are 7,407 languages in the world. But, what about the languages that are not there in the world? Are humans so narrow minded that we don't care ab
arXiv:2604.22526v1 Announce Type: new Abstract: Wireless localization of permanent magnets enables occlusion-free guidance for medical interventions, yet its practical accuracy is fundamentally limite
arXiv:2601.17060v2 Announce Type: replace-cross Abstract: Artificially intelligent systems have become remarkably sophisticated. They hold conversations, write essays, and seem to understand context i
arXiv:2604.22081v1 Announce Type: new Abstract: Most reinforcement-learning (RL) controllers used in continuous control are architecturally centralized: observations are compressed into a single laten