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arXiv:2601.20554v1 Announce Type: new Abstract: We study risk-sensitive planning under partial observability using the dynamic risk measure Iterated Conditional Value-at-Risk (ICVaR). A policy evaluation algorithm...
arXiv:2601.20555v1 Announce Type: new Abstract: Rich contact perception is crucial for robotic manipulation, yet traditional tactile skins remain expensive and complex to integrate. This paper...
arXiv:2601.20556v1 Announce Type: new Abstract: Unsupervised ensemble learning emerged to address the challenge of combining multiple learners' predictions without access to ground truth labels or...
arXiv:2601.20561v1 Announce Type: new Abstract: Transmission electron microscopes (TEMs) enable atomic-scale imaging but suffer from aberrations caused by lens imperfections and environmental conditions, reducing image...
arXiv:2601.20564v1 Announce Type: new Abstract: The practical deployment of diffusion-based Neural Video Compression (NVC) faces critical challenges, including severe information loss, prohibitive inference latency, and...
arXiv:2601.20566v1 Announce Type: new Abstract: This paper investigates the time fractional sine-Gordon equation whose solution exhibits a weak singularity of type t^{\alpha}. By means of...
arXiv:2601.20568v1 Announce Type: new Abstract: During pretraining, LLMs inadvertently memorize sensitive or copyrighted data, posing significant compliance challenges under legal frameworks like the GDPR and...
arXiv:2601.20571v1 Announce Type: new Abstract: Specifications for decentralized learning on resource-constrained edge devices require algorithms that are communication-efficient, robust to data corruption, and lightweight in...
arXiv:2601.20573v1 Announce Type: new Abstract: Speech emotion recognition (SER) is crucial in speech understanding and generation. Most approaches are based on either classification models or...
arXiv:2601.20577v1 Announce Type: new Abstract: Multi-robot systems have been widely deployed in real-world applications, providing significant improvements in efficiency and reductions in labor costs. However,...
arXiv:2601.20578v1 Announce Type: new Abstract: Who benefits from expanding transport networks? While designed to improve mobility, such interventions can also create inequality. In this paper,...
arXiv:2601.20580v1 Announce Type: new Abstract: Dependability - a system's ability to consistently provide reliable services by ensuring safety and maintainability in the face of internal...
arXiv:2601.20582v1 Announce Type: new Abstract: Spontaneous symmetry breaking in statistical mechanics primarily occurs during phase transitions at the thermodynamic limit where the Hamiltonian preserves inversion...
arXiv:2601.20583v1 Announce Type: new Abstract: We study an inverse scattering problem for monostatic synthetic aperture radar (SAR): Estimate the wave speed in a heterogeneous, isotropic...
arXiv:2601.20585v1 Announce Type: new Abstract: Ordinal regression and ranking are challenging due to inherent ordinal dependencies that conventional methods struggle to model. We propose Ranking-Aware...
arXiv:2601.20586v1 Announce Type: new Abstract: Massive multiple-input multiple-output (mMIMO) technology and its future evolutions are expected to address the high data rate demands of sixth...
arXiv:2601.20592v1 Announce Type: new Abstract: We investigate structural traces of language contact in the intermediate representations of a monolingual language model. Focusing on Persian (Farsi)...
arXiv:2601.20595v1 Announce Type: new Abstract: Communication has become a first-order bottleneck in large-cale GPU workloads, and existing distributed compilers address it mainly by overlapping whole...
arXiv:2601.20597v1 Announce Type: new Abstract: Continual Text-to-Video Retrieval (CTVR) is a challenging multimodal continual learning setting, where models must incrementally learn new semantic categories while...
arXiv:2601.20598v1 Announce Type: new Abstract: Person Re-Identification (ReID) remains a challenging problem in computer vision. This work reviews various training paradigm and evaluates the robustness...
arXiv:2601.20599v1 Announce Type: new Abstract: Gradient temporal-difference (GTD) learning algorithms are widely used for off-policy policy evaluation with function approximation. However, existing convergence analyses rely...
arXiv:2601.20600v1 Announce Type: new Abstract: In the recent years, there has been active research on self-orthogonal embeddings of linear codes since they yielded some optimal...
arXiv:2601.20601v1 Announce Type: new Abstract: Medical image classification is a core task in computer-aided diagnosis (CAD), playing a pivotal role in early disease detection, treatment...
arXiv:2601.20604v1 Announce Type: new Abstract: This paper introduces a methodological framework for empirically testing AI alignment strategies through structured multi-model dialogue. Drawing on Peace Studies...