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arXiv:2603.15668v1 Announce Type: new Abstract: As agentic artificial intelligence systems scale across globally distributed and long lived infrastructures, secure and policy compliant communication becomes a …
arXiv:2603.15666v1 Announce Type: new Abstract: Existing memory systems for language agents address memory management: how to retrieve and page more information within a context budget. …
arXiv:2603.15968v1 Announce Type: new Abstract: Constitutional AI is a method to oversee and control LLMs based on a set of rules written in natural language. …
arXiv:2603.15653v1 Announce Type: new Abstract: Long-context handling remains a core challenge for language models: even with extended context windows, models often fail to reliably extract, …
arXiv:2603.15799v1 Announce Type: new Abstract: Prose2Policy (P2P) is a LLM-based practical tool that translates natural-language access control policies (NLACPs) into executable Rego code (the policy …
arXiv:2603.15633v1 Announce Type: new Abstract: Answering complex first-order logic (FOL) queries on knowledge graphs is essential for reasoning. Symbolic methods offer interpretability but struggle with …
arXiv:2603.15674v1 Announce Type: new Abstract: We present a complete theoretical characterization of Latent Posterior Factors (LPF), a principled framework for aggregating multiple heterogeneous evidence items …
arXiv:2603.15994v1 Announce Type: new Abstract: Retrieval-augmented generation stores all content indiscriminately, degrading accuracy as noise accumulates. Parametric approaches compress knowledge into weights, precluding selective updates. …
arXiv:2603.16210v1 Announce Type: new Abstract: Safety alignment in large language models (LLMs) is commonly implemented as a single static policy embedded in model parameters. However, …
arXiv:2603.16313v1 Announce Type: new Abstract: Electronic control units (ECUs) embedded within modern vehicles generate a large number of asynchronous events known as diagnostic trouble codes …
arXiv:2603.15946v1 Announce Type: new Abstract: Computational argumentation offers formal frameworks for transparent, verifiable reasoning but has traditionally been limited by its reliance on domain-specific information …
arXiv:2603.15998v1 Announce Type: new Abstract: Occupations form and evolve faster than classification systems can track. We propose that a genuine occupation is a self-reinforcing structure …