Some enterprises might find that upgrading to newer, more expensive PCs is worth the investment since it appears cheap PCs won’t be coming anytime soon, analysts said.
Dell and HP both have announced new business PCs that run …
arXiv:2509.19162v2 Announce Type: replace-cross
Abstract: This is the third paper of the CayleyPy project applying artificial intelligence to problems in group theory. We announce the first public release of CayleyPy, an open source Python library for…
arXiv:2604.00422v1 Announce Type: cross
Abstract: DNNs are susceptible to defects like backdoors, adversarial attacks, and unfairness, undermining their reliability. Existing approaches mainly involve retraining, optimization, constraint-solving, or s…
arXiv:2604.00641v1 Announce Type: cross
Abstract: We propose a novel extension of the Bradley-Terry model to multiplayer games and adapt a recent algorithm by Newman [1] to our model. We demonstrate the use of our proposed method on synthetic datasets…
arXiv:2604.00860v1 Announce Type: new
Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a central post-training paradigm for improving the reasoning capabilities of large language models. Yet existing methods share a common bl…
arXiv:2604.00918v1 Announce Type: new
Abstract: Spectral graph neural networks learn graph filters, but their behavior with increasing depth and polynomial order is not well understood. We analyze these models in the graph Fourier domain, where each l…
arXiv:2604.01197v1 Announce Type: cross
Abstract: Learning quantum states from measurement data is a central problem in quantum information and computational complexity. In this work, we study the problem of learning to generate mixed states on a fini…
arXiv:2508.09281v3 Announce Type: replace
Abstract: Personalized instruction aims to provide learners with support that adapts to their individual knowledge and progress toward learning objectives. Discovering and tracing Knowledge Components (KCs) is…
arXiv:2603.10305v2 Announce Type: replace
Abstract: Machine learning models can represent climate processes that are nonlocal in horizontal space, height, and time, often by combining information across these dimensions in highly nonlinear ways. While…
arXiv:2603.22455v4 Announce Type: replace
Abstract: Reusable skills let LLM agents package task-specific procedures, tool affordances, and execution guidance into modular building blocks. As skill ecosystems grow to tens of thousands of entries, expos…