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arXiv:2602.17217v1 Announce Type: new Abstract: Efficiently navigating complex environments requires agents to internalize the underlying logic of their world, yet standard world modelling methods often...
arXiv:2602.17221v1 Announce Type: new Abstract: Generative AI is reshaping knowledge work, yet existing research focuses predominantly on software engineering and the natural sciences, with limited...
arXiv:2602.17222v1 Announce Type: new Abstract: Predicting human decision-making in high-stakes environments remains a central challenge for artificial intelligence. While large language models (LLMs) demonstrate strong...
arXiv:2602.17223v1 Announce Type: new Abstract: As large language models (LLMs) continue to grow in size, fewer users are able to host and run models locally....
arXiv:2602.17226v1 Announce Type: new Abstract: Operating in previously visited environments is becoming increasingly crucial for autonomous systems, with direct applications in autonomous driving, surveying, and...
arXiv:2602.17229v1 Announce Type: new Abstract: The black-box nature of Large Language Models necessitates novel evaluation frameworks that transcend surface-level performance metrics. This study investigates the...
arXiv:2602.17231v1 Announce Type: new Abstract: Accurate motion forecasting is critical for autonomous driving, yet most predictors rely on multi-object tracking (MOT) with identity association, assuming...
arXiv:2602.17234v1 Announce Type: new Abstract: To evaluate whether LLMs can accurately predict future events, we need the ability to \textit{backtest} them on events that have...
arXiv:2602.17237v1 Announce Type: new Abstract: We introduce a compositional approach to model-based test generation in Behavior-Driven Development (BDD). BDD is an agile methodology in which...
arXiv:2602.17239v1 Announce Type: new Abstract: Electrified heating systems with thermal storage, such as electric boilers and heat pumps, represent a major source of demand-side flexibility....
arXiv:2602.17242v1 Announce Type: new Abstract: We introduce \emph{TAPO-Structured Description Logic} (TAPO--DL), a formal extension of classical description logic designed to model \emph{information behavior} as a...
arXiv:2602.17244v1 Announce Type: new Abstract: Counterfactual explanations (CFs) provide human-interpretable insights into model's predictions by identifying minimal changes to input features that would alter the...
arXiv:2602.17245v1 Announce Type: new Abstract: The Web is evolving from a medium that humans browse to an environment where software agents act on behalf of...
arXiv:2602.17247v1 Announce Type: new Abstract: This paper investigates goal-oriented remote monitoring of an unobservable Markov source using energy-harvesting sensors that communicate with a mobile receiver,...
arXiv:2602.17250v1 Announce Type: new Abstract: This study investigates whether the geospatial and multimodal features encoded in \textit{Earth Embeddings} can effectively guide deep learning (DL) regression...
arXiv:2602.17251v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models (EFMs) have achieved strong performance under full fine-tuning but exhibit poor generalization when subject-level supervision is...
arXiv:2602.17252v1 Announce Type: new Abstract: Freight vehicles approaching signalized intersections require reliable detection and motion estimation to support infrastructure-based Freight Signal Priority (FSP). Accurate and...
arXiv:2602.17254v1 Announce Type: new Abstract: AllReduce is a fundamental collective operation in distributed computing and a key performance bottleneck for large-scale training and inference. Its...
arXiv:2602.17259v1 Announce Type: new Abstract: Enabling VLA models to predict environmental dynamics, known as world modeling, has been recognized as essential for improving robotic reasoning...
arXiv:2602.17260v1 Announce Type: new Abstract: Recent advances in foundation video generators such as Sora2, Veo3, and other commercial systems have produced highly realistic synthetic videos,...
arXiv:2602.17262v1 Announce Type: new Abstract: Human self-report questionnaires are increasingly used in NLP to benchmark and audit large language models (LLMs), from persona consistency to...
arXiv:2602.17263v1 Announce Type: new Abstract: Controlling the longitudinal laser pulse shape in photoinjectors of Free-Electron Lasers is a powerful lever for optimizing electron beam quality,...
arXiv:2602.17264v1 Announce Type: new Abstract: User-centric evaluation has become a key paradigm for assessing Conversational Recommender Systems (CRS), aiming to capture subjective qualities such as...
arXiv:2602.17270v1 Announce Type: new Abstract: We present Unified Latents (UL), a framework for learning latent representations that are jointly regularized by a diffusion prior and...