Quality follows upgrading
Category
arXiv:2603.11388v1 Announce Type: new Abstract: Safety alignment aims to ensure that large language models (LLMs) refuse harmful requests by post-training on harmful queries paired with …
arXiv:2603.11382v1 Announce Type: new Abstract: Autonomous agents, especially delegated systems with memory, persistent context, and multi-step planning, pose a measurement problem not present in stateless …
arXiv:2603.11353v1 Announce Type: new Abstract: Many assumptions that underpin human concepts of identity do not hold for machine minds that can be copied, edited, or …
arXiv:2603.11352v1 Announce Type: new Abstract: Transformer-based time series foundation models face a fundamental trade-off in choice of tokenization: point-wise embeddings preserve temporal fidelity but scale …
arXiv:2603.11340v1 Announce Type: new Abstract: In this paper, we present a novel black-box online controller that uses only end-to-end measurements over short segments, without internal …
arXiv:2603.11339v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied to financial analysis, yet their ability to audit structured financial statements under explicit …
arXiv:2603.11337v1 Announce Type: new Abstract: LLM agents increasingly perform end-to-end ML engineering tasks where success is judged by a single scalar test metric. This creates …
arXiv:2603.11333v1 Announce Type: new Abstract: Short-video platforms are closed-loop, human-in-the-loop ecosystems where platform policy, creator incentives, and user behavior co-evolve. This feedback structure makes counterfactual …
arXiv:2603.11299v1 Announce Type: new Abstract: This editorial addresses the critical intersection of artificial intelligence (AI) and blockchain technologies, highlighting their contrasting tendencies toward centralization and …
arXiv:2603.11279v1 Announce Type: new Abstract: The immense number of parameters and deep neural networks make large language models (LLMs) rival the complexity of human brains, …
arXiv:2603.11277v1 Announce Type: new Abstract: The rapid proliferation of large language model (LLM)-based agentic systems raises critical concerns regarding digital sovereignty, environmental sustainability, regulatory compliance, …
arXiv:2603.11266v1 Announce Type: new Abstract: Unlearning in Large Language Models (LLMs) aims to enhance safety, mitigate biases, and comply with legal mandates, such as the …