Knowledge catalogue
arXiv:2608.14792v1 Announce Type: cross Abstract: Objectives: To determine whether zero-shot prompting of a large language model (LLM) is sufficient to detect shared decision-making (SDM) behaviors in
arXiv:2608.15746v1 Announce Type: new Abstract: We present a forensic analysis of the generation pipeline behind a recent AI-driven influence campaign. We introduce PROPAGIA, a corpus of 2,646 propaga
arXiv:2608.16094v1 Announce Type: new Abstract: Accurate protein structure prediction is fundamental to structural biology because protein structure underlies molecular function and provides a basis f
arXiv:2508.07345v2 Announce Type: replace-cross Abstract: extbf{Introduction:} Accurate prediction of Phage Virion Proteins (PVP) is essential for genomic studies due to their crucial role as structur
arXiv:2608.16844v1 Announce Type: cross Abstract: The quadratic cost of attention-based sequence models for long contexts has motivated a growing line of research on memory-based models that can compr
arXiv:2608.15037v1 Announce Type: cross Abstract: Audio-Text Foundation Models (ATMs) fail catastrophically under severe acoustic noise, yet existing adaptation strategies either rely on gradient-base
arXiv:2608.15761v1 Announce Type: cross Abstract: Edge-IIoTset is the reference benchmark for machine-learning intrusion detection in the industrial Internet of Things, and results reported on it clus
arXiv:2608.15146v1 Announce Type: new Abstract: We revisit Tesauro's TD-Gammon for backgammon money games in the setting of no evaluation-time search. Both checker play and cube action (use of the dou
arXiv:2608.14652v1 Announce Type: cross Abstract: The development of 0.1^{irc} global weather forecasting models based on machine learning (ML) is constrained by the limited availability of high-resol
arXiv:2608.15802v1 Announce Type: new Abstract: Out-of-distribution (OOD) detection remains challenging for image classifiers, especially when near-OOD samples lie close to in-distribution (ID) class
arXiv:2608.16888v1 Announce Type: new Abstract: The development of safe and beneficial AI requires that systems can learn and act in accordance with human preferences. However, explicitly specifying t
arXiv:2601.02754v3 Announce Type: replace-cross Abstract: With the rapid development of e-commerce, auto-bidding has become a key asset in optimizing advertising performance under diverse advertiser e
arXiv:2601.03506v2 Announce Type: replace-cross Abstract: Recent large reasoning models (LRMs) have achieved strong performance on complex reasoning tasks by generating a long chain-of-thought (Long-C
arXiv:2608.15492v1 Announce Type: new Abstract: Finding representative waveforms in long time series has scientific and practical value in many domains, as it enables summarization and visualization o
arXiv:2608.14664v1 Announce Type: new Abstract: How can we determine whether a trained neural network is already deep enough? We study this under a fixed function-preserving residual-growth protocol s
arXiv:2608.16212v1 Announce Type: new Abstract: Laboratory battery tests provide the main empirical basis for battery performance and degradation studies, but their operating patterns do not directly
arXiv:2410.17397v2 Announce Type: replace-cross Abstract: We introduce a framework for seamlessly integrating quantum computing into pretrained large language models (LLMs). The key idea is to constru
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:2608.15820v1 Announce Type: new Abstract: We present QuantumPhaseNet, a gauge-covariant geometric and quantum-spectral extension of Transformer representations. Context-dependent semantic states
arXiv:2608.16813v1 Announce Type: new Abstract: Agents now write knowledge graphs, but knowledge-graph stores still carry defaults set when humans curated them: accept writes now and clean later, keep
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:2608.14790v1 Announce Type: new Abstract: Instruction-based video editing is commonly built on video-pretrained generative backbones: a video diffusion transformer is adapted, at considerable co
arXiv:2608.16033v1 Announce Type: new Abstract: In cognitive science, resource rationality asks how an agent should allocate limited computation to maximize expected value. Most reasoning and agent be
arXiv:2608.16167v1 Announce Type: cross Abstract: High-precision radio map construction is essential for emerging 6G Integrated Sensing and Communication (ISAC) applications, including digital twins a
arXiv:2608.15857v1 Announce Type: new Abstract: Ethereum is now integral to mission-critical sectors, including finance, healthcare, and supply chain management. Execution fees, commonly referred to a
arXiv:2608.16018v1 Announce Type: cross Abstract: Graph anomaly detection aims to identify nodes that deviate from normal behavioral patterns within graphs. However, existing methods largely rely on t
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:2608.14999v1 Announce Type: cross Abstract: Constructing special graphs is an important task within graph theory and computer science. Many popular graph constructions are the result of a compre
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:2608.16664v1 Announce Type: cross Abstract: We study the Random Quadratic Form (RQF) on a sphere in the presence of random Brownian forcing. We show that the forcing does not effectively change
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:2608.15924v1 Announce Type: new Abstract: Cloud-side inference gives imitation-learning policies access to greater computational resources, but communication and computation delays can degrade c
arXiv:2608.16335v1 Announce Type: new Abstract: Allocation schemes that greedily maximize a readiness metric over the actuator fiber bundle of an overactuated multirotor produce commands that jump bet
arXiv:2608.14865v1 Announce Type: new Abstract: An actuator health estimation algorithm for a soft swimming robot that can perform anguilliform swimming is developed. Due to harsh operational environm
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:2608.15291v1 Announce Type: new Abstract: Demand forecasting increasingly requires combining two complementary sources of information: historical sales reveal recurring numerical dynamics, while
arXiv:2602.21219v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) personalization holds great promise for tailoring responses by leveraging personal context and history. However, re
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:2608.16645v1 Announce Type: new Abstract: Can a language model recover the true research idea of a published paper when given only that paper's pre-publication bibliography? We introduce Reconst
arXiv:2509.12757v2 Announce Type: replace Abstract: Cross-view object geo-localization (CVOGL) aims to determine the location of a specific object in high-resolution satellite imagery given a query im
arXiv:2608.15062v1 Announce Type: new Abstract: Scaling transformer language models creates an inherent tension between expressivity and memory efficiency. While unique weights across layers preserve
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:2608.16155v1 Announce Type: new Abstract: In over-the-counter corporate bond markets, dealers compete for client trades by quoting bid and ask prices. Tighter quotes attract more business, but a
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:2608.15138v1 Announce Type: new Abstract: Designing an ABR algorithm for one network scenario takes an engineer months, and large language models now do this work in hours, matching or beating h
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:2608.16087v1 Announce Type: new Abstract: Removing wearables from physiological monitoring also removes their supervision: the signal indicating where and when a stress response occurred. Contac
arXiv:2608.16011v1 Announce Type: new Abstract: We introduce ReRef-3D, a benchmark for language-guided placement in 3D scenes. It contains 33,826 instructions across 998 CLEVR-derived scenes, spanning
arXiv:2608.15889v1 Announce Type: cross Abstract: Currency arbitrage (CA) involves trading currencies in cycles to exploit discrepancies in market valuations. Quadratic unconstrained binary optimizati
arXiv:2608.14685v1 Announce Type: new Abstract: Knowledge distillation (KD) is widely used to transfer the capabilities of large language models (LLMs) to smaller students, but existing objectives oft
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:2608.14947v1 Announce Type: new Abstract: Detecting opioid craving from wearable physiological signals is critical yet difficult, with the potential to support proactive interventions for indivi
arXiv:2608.16005v1 Announce Type: new Abstract: This paper studies the problem of molecule-text alignment, which aims to project molecules and their textual descriptions into a joint latent space for
arXiv:2608.16111v1 Announce Type: cross Abstract: Retrosynthesis is a cornerstone of drug discovery and organic synthesis. While data-driven deep learning models have shown remarkable progress, they a
arXiv:2608.16786v1 Announce Type: new Abstract: Inference-time quality-enhancement methods are an effective and widely adopted means of improving diffusion models without expensive retraining. We stud
arXiv:2608.15938v1 Announce Type: new Abstract: Action chunking --- the practice of predicting a sequence of actions and executing a prefix open-loop --- has emerged as a key enabler of recent progres