Knowledge catalogue
arXiv:2609.04981v1 Announce Type: new Abstract: Recent structured RAG methods leverage tree- or graph-based reasoning structures to improve multi-hop QA. However, they face key limitations in evidence
arXiv:2609.05251v1 Announce Type: new Abstract: We present a unified reinforcement-learning (RL) framework that discovers compact parametrized quantum circuits (PQCs) for data-scarce device modeling.
arXiv:2609.05221v1 Announce Type: cross Abstract: Large language models (LLMs) show strong reasoning ability, but their explanations can remain inconsistent, weakly grounded, or difficult to verify. W
arXiv:2609.04303v1 Announce Type: cross Abstract: Information abstraction, which groups strategically similar private states into a tractable number of buckets, is essential for scaling game-solving a
arXiv:2609.05228v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures provide an efficient paradigm for scaling large language models (LLMs), yet fixed top-k routing activates the sam
arXiv:2609.04464v1 Announce Type: new Abstract: Sampling-based motion planning algorithms are a popular class of trajectory planning algorithm due to their speed in complex, high-dimensional environme
arXiv:2510.17450v2 Announce Type: replace Abstract: We develop an active inference route-planning method for the autonomous control of intelligent agents. The aim is to reconnoiter a geographical area
arXiv:2609.04901v1 Announce Type: cross Abstract: Tabular foundation models (TabFMs) achieve strong performance on structured data, particularly for standard classification and regression problems. Ye
arXiv:2609.05331v1 Announce Type: new Abstract: Robotic systems increasingly operate in dynamic, uncertain, and open-ended environments, where design-time assumptions may no longer hold, and adaptatio
arXiv:2609.04350v1 Announce Type: cross Abstract: How do people learn to become better conversationalists? This question is especially important in the context of mental-health counseling, where conve
arXiv:2609.05320v1 Announce Type: new Abstract: Deepfake detection models often rely on high-quality inputs, fixed inference paths, and computationally expensive architectures, limiting their use in l
arXiv:2609.05066v1 Announce Type: cross Abstract: As the scale of video surveillance data outpaces manual annotation capacities, weakly supervised video anomaly detection (WSVAD) has emerged as a crit
arXiv:2609.04369v1 Announce Type: new Abstract: Visual Place Recognition (VPR) localizes a query image by retrieving database images of the same or nearby place, yet its robustness is often degraded b
arXiv:2609.05270v1 Announce Type: new Abstract: Artificial intelligence (AI) is transforming not only what information systems researchers design, but also how design research is conducted. Yet existi
arXiv:2501.10396v4 Announce Type: replace-cross Abstract: We present methods and applications for the development of digital twins (DT) for urban traffic management. While the majority of studies on t
arXiv:2609.03693v1 Announce Type: cross Abstract: Large language models (LLMs) are vulnerable to jailbreak attacks that bypass safety alignment through carefully crafted prompts. Many existing defense
arXiv:2502.17295v2 Announce Type: replace-cross Abstract: Team communication breakdowns represent a contributor to patient safety risks within action teams-defined as interdependent groups of speciali
arXiv:2609.05016v1 Announce Type: cross Abstract: Scaling laws guide the design choices for training large foundation models, but deriving them involves training an exhaustive grid over hyperparameter
arXiv:2609.05031v1 Announce Type: cross Abstract: Self-supervised learning relies on so-called data augmentations phi(x) of unlabeled datapoints x --- for example, masking random pixels in an image x
arXiv:2609.04791v1 Announce Type: new Abstract: Lesion-focused image classification presents a core analytical challenge, as discriminative signals are often sparse, spatially dispersed, and easily ob
arXiv:2406.02465v2 Announce Type: replace-cross Abstract: Can pretrained models generalize to new datasets without any retraining? We deploy pretrained image models on datasets they were not trained f
arXiv:2609.04530v1 Announce Type: new Abstract: We develop an energy-based reduced-order model for micromagnetic magnetization dynamics that couples a convolutional autoencoder to a structured latent
arXiv:2609.04603v1 Announce Type: new Abstract: Recent generative image-editing Diffusion Transformers (DiTs) demonstrate impressive semantic editing capabilities but still struggle with spatially con
arXiv:2602.14941v2 Announce Type: replace-cross Abstract: Maintaining spatial world consistency over long horizons remains a central challenge for camera-controllable video generation. Existing memory
arXiv:2609.04709v1 Announce Type: new Abstract: Text-guided diffusion editing raises disinformation concerns, making reliable image provenance essential. While watermarks are commonly used for this pu
arXiv:2609.05161v1 Announce Type: cross Abstract: Rigid Body Dynamics (RBD) forms the computational core of real-time robotic control, but its immense computational complexity creates a performance bo
arXiv:2609.04738v1 Announce Type: new Abstract: In this paper, we study the problem of personalized survey response prediction using fine-tuned large language models (LLMs). This task poses unique cha
arXiv:2609.04411v1 Announce Type: cross Abstract: Autonomous underwater robots are widely used for exploration, monitoring, and inspection, where safe navigation depends on understanding the surroundi
arXiv:2609.04965v1 Announce Type: new Abstract: Cross-view localization (CVL) estimates the pose of a ground image by matching it to a geo-referenced satellite image. To bridge the extreme viewpoint g
arXiv:2609.04913v1 Announce Type: cross Abstract: Automotive infotainment validation still relies on manual testing, slow, costly, and incompatible with agile releases and OTA updates. Scripted automa
arXiv:2609.04917v1 Announce Type: new Abstract: Artificial intelligence (AI) now supports investment workflows from data and prediction through research, portfolios, execution, and tool use. Technical
arXiv:2609.05258v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to formulate optimization models from natural-language problem descriptions, yet realistic operatio
arXiv:2609.04513v1 Announce Type: cross Abstract: Compound AI workflows are increasingly used to serve complex AI tasks by coordinating multiple AI models and software components. This approach enable
arXiv:2609.04891v1 Announce Type: cross Abstract: Four-dimensional (4D) flow magnetic resonance imaging (MRI) is a powerful non-invasive technique for visualizing and quantifying complex blood flow pa
arXiv:2609.04611v1 Announce Type: new Abstract: LLM agents are rapidly becoming production software, deployed to handle customer service, adjudicate disputes, and operate internal systems. Notably, th
arXiv:2609.04206v1 Announce Type: cross Abstract: Voice AI systems increasingly mediate customer care interactions where caller presentation cues such as accent, affect, fluency, and urgency are avail
arXiv:2609.04871v1 Announce Type: new Abstract: Improving an industrial recommender is an iterative research-and-engineering process rather than a direct path from idea to deployment. In extbf{DASHEN,
arXiv:2609.04232v1 Announce Type: cross Abstract: This paper offers a unique perspective on how speech technologies are being adopted by community-led heritage language preservation and revitalisation
arXiv:2603.23723v3 Announce Type: replace-cross Abstract: Deep spatially selective filters achieve high-quality enhancement with real-time capable architectures for stationary speakers of known direct
arXiv:2609.04253v1 Announce Type: cross Abstract: Audio-video (AV) editing aims to modify audio and video content according to a target prompt. Unlike single-modality editing, AV editing requires mode
arXiv:2609.05157v1 Announce Type: cross Abstract: Formalizing mathematics in a proof assistant, where a machine checks every definition, statement and proof, has set a new standard of rigor. Large lan
arXiv:2609.04971v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) achieve superior problem-solving through extended Chain-of-Thought (CoT) generation, but the resulting key-value (KV) ca
arXiv:2609.04747v1 Announce Type: cross Abstract: To enable accurate and rapid photon control point and proton beamlet dose calculation in the DoseRAD2026 challenge, we present BEAM3R, a dose estimati
arXiv:2609.04753v1 Announce Type: new Abstract: Reasoning in large language models unfolds through diverse functional operations, such as problem formulation, goal decomposition, and deduction. Althou
arXiv:2609.04292v1 Announce Type: new Abstract: Human mobility predictability concerns the best prediction performance attainable from a given target and input information, but its ground truth is not
arXiv:2609.04909v1 Announce Type: cross Abstract: Large language models (LLMs) have significantly advanced automated program repair (APR), yet existing evaluations remain largely result-centric and pr
arXiv:2609.04425v1 Announce Type: new Abstract: Forecasting-model selection remains difficult in heterogeneous demand because the most suitable decision rule may vary with demand structure, data avail
arXiv:2609.05289v1 Announce Type: new Abstract: Automated reference-based evaluation methods play a critical role in assessing natural language generation systems. Existing meta-evaluation primarily m
arXiv:2609.05063v1 Announce Type: cross Abstract: When a customer adds a professional camera to their cart, should the system suggest a matching lens, a generic tripod, or another camera body? Complem
arXiv:2609.04681v1 Announce Type: cross Abstract: AI coding systems are moving from autocomplete and chat toward agents that can inspect repositories, edit multiple files, run tools, write tests, open
arXiv:2609.04995v1 Announce Type: new Abstract: Deep Imbalanced Regression (DIR) is pervasive in continuous prediction tasks across diverse modalities, such as age estimation, depth prediction, and pr
arXiv:2609.05150v1 Announce Type: cross Abstract: This paper introduces Regime-aware Constraint-Based and Noise-Based causal discovery with Markov Blankets (RCBNB-MB), a novel causal discovery algorit
arXiv:2609.04504v1 Announce Type: new Abstract: Cardiac, neural, behavioral, and speech measurements from wearable and mobile devices provide partial, noise-sensitive views of physiological state. Bio
arXiv:2609.04999v1 Announce Type: new Abstract: This paper describes the participation of the BIT.UA team from the University of Aveiro in the 14th edition of the BioASQ Task B challenge on biomedical
arXiv:2609.05210v1 Announce Type: new Abstract: Recent hybrid Structure-from-Motion (SfM) systems combine the robustness of feed-forward 3D reconstruction with the accuracy of traditional bundle adjus
arXiv:2609.04356v1 Announce Type: cross Abstract: This paper analyzes the implementation of blockchain-based integrity mechanisms in Greek Fiscal Electronic Mechanisms (FEMs) and the central tax infor
arXiv:2602.11558v2 Announce Type: replace Abstract: Brain foundation models (BFMs) are advancing neurotechnology by learning transferable representations from neural signals, with broad potential in c
arXiv:2609.04726v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) images have all-weather, day-and-night observation capabilities. However, compared with optical images, their speckle noi
arXiv:2609.04711v1 Announce Type: cross Abstract: Generative AI and coding agents can accelerate research software development, but they also increase the need for efficient software discovery and mai
arXiv:2609.05227v1 Announce Type: new Abstract: Recent reports during the AAAI-27 review cycle highlight the risk of reviewers coordinating bids for reciprocal assignment advantage. Prior work treats