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arXiv:2604.04043v1 Announce Type: new Abstract: Recent work has shown that fine-tuning large language models (LLMs) on insecure code or culturally loaded numeric codes can induce …
arXiv:2604.03571v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) generate structured chains of thought (CoTs) before producing final answers, making them especially vulnerable to knowledge …
arXiv:2604.03656v1 Announce Type: new Abstract: Generative Engine Optimization (GEO) is rapidly reshaping digital marketing paradigms in the era of Large Language Models (LLMs). However, current …
arXiv:2604.03616v1 Announce Type: new Abstract: Asking a large language model to respond in JSON should be a formatting choice, not a capability tax. Yet we …
arXiv:2604.03512v1 Announce Type: new Abstract: Outage management in large-scale cloud operations remains heavily manual, requiring rapid triage, cross-team coordination, and experience-driven decisions under partial observability. …
arXiv:2604.03240v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by grounding generation in external knowledge, yielding relevance responses that are aligned …
arXiv:2604.03588v1 Announce Type: new Abstract: AI agents operating over extended time horizons accumulate experiences that serve multiple concurrent goals, and must often maintain conflicting interpretations …
arXiv:2604.03858v1 Announce Type: new Abstract: Training Data Attribution (TDA) seeks to trace model predictions back to influential training examples, enhancing interpretability and safety. We formulate …
arXiv:2604.04131v1 Announce Type: new Abstract: Large language model agents that use external tools are often implemented through reactive execution, in which reasoning is repeatedly recomputed …
arXiv:2604.03478v1 Announce Type: new Abstract: In high-stakes settings where machine learning models are used to automate decision-making about individuals, the presence of algorithmic bias can …
arXiv:2604.03904v1 Announce Type: new Abstract: Large language models (LLMs) frequently produce confident but incorrect answers, partly because common binary scoring conventions reward answering over honestly …
arXiv:2604.04145v1 Announce Type: new Abstract: Photovoltaic (PV) power forecasting plays a critical role in power system dispatch and market participation. Because PV generation is highly …