Quality follows upgrading
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arXiv:2604.02361v1 Announce Type: cross Abstract: Detecting Internet routing instability is a critical yet challenging task, particularly when relying solely on endpoint active measurements. This study …
arXiv:2604.02353v1 Announce Type: cross Abstract: We present PRISM (Policy Reuse via Interpretable Strategy Mapping), a framework that grounds reinforcement learning agents' decisions in discrete, causally …
arXiv:2604.02615v1 Announce Type: new Abstract: Graph neural networks (GNNs) are a well-regarded tool for learned control of networked dynamical systems due to their ability to …
arXiv:2604.02881v1 Announce Type: new Abstract: Weight-space model merging combines independently fine-tuned models without accessing original training data, offering a practical alternative to joint training. While …
arXiv:2604.02341v1 Announce Type: cross Abstract: Mathematical reasoning in large language models has improved substantially with reinforcement learning using verifiable rewards, where final answers can be …
arXiv:2604.02577v1 Announce Type: new Abstract: We introduce ROMAN (ROuting Multiscale representAtioN), a deterministic operator for time series that maps temporal scale and coarse temporal position …
arXiv:2604.02340v1 Announce Type: new Abstract: Recent advances in masked diffusion language models (MDLMs) narrow the quality gap to autoregressive LMs, but their sampling remains expensive …
arXiv:2604.02358v1 Announce Type: cross Abstract: Vehicular Ad Hoc Networks (VANETs) play a crucial role in realizing vehicle-road collaboration and intelligent transportation. However, urban VANETs often …
arXiv:2604.02954v1 Announce Type: new Abstract: Graph-based Retrieval-Augmented Generation (GraphRAG) enhances the reasoning capabilities of Large Language Models (LLMs) by grounding their responses in structured knowledge …
arXiv:2604.02359v1 Announce Type: cross Abstract: General-purpose Large Language Models (LLMs) are becoming widely adopted by people for mental health support. Yet emerging evidence suggests there …
arXiv:2604.02378v1 Announce Type: new Abstract: Forecasting startup success is notoriously difficult, partly because meaningful outcomes, such as exits, large funding rounds, and sustained revenue growth, …
arXiv:2604.02721v1 Announce Type: new Abstract: Competitive programming remains one of the last few human strongholds in coding against AI. The best AI system to date …