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arXiv:2603.26782v1 Announce Type: new Abstract: Texttolevel generation aims to translate natural language descriptions into structured game levels, enabling intuitive control over procedural content generation.
arXiv:2603.26838v1 Announce Type: new Abstract: This paper surveys uncertaintyaware explainable artificial intelligence UAXAI, examining how uncertainty is incorporated into explanatory pipelines and how such methods are evaluated.
arXiv:2603.26944v1 Announce Type: new Abstract: Predictive modeling on sequential event data is critical for fraud detection and healthcare monitoring.
arXiv:2603.26948v1 Announce Type: new Abstract: Existing approaches for predictive process monitoring are subsymbolic, meaning that they learn correlations between descriptive features and a target feature fully based on data, e.g.
arXiv:2603.26983v1 Announce Type: new Abstract: Art. 50 II of the EU Artificial Intelligence Act mandates dual transparency for AIgenerated content: outputs must be labeled in both humanunderstandable and machinereadable form for automated verification.
arXiv:2603.26996v1 Announce Type: new Abstract: We present FormalProofBench, a private benchmark designed to evaluate whether AI models can produce formally verified mathematical proofs at the graduate level.
arXiv:2603.27076v1 Announce Type: new Abstract: Large language models LLMs are increasingly used for automated tutoring, but their reliability in structured symbolic domains remains unclear.
arXiv:2603.27116v1 Announce Type: new Abstract: Every major AI memory system in production today organises information by meaning. That organisation enables generalisation, analogy, and conceptual retrieval but it comes at a price.
arXiv:2603.27150v1 Announce Type: new Abstract: Large language models LLMs have revolutionized medical reasoning tasks, yet singleagent systems often falter on complex, interdisciplinary problems requiring robust handling of uncertainty and conflicting evidence.
TRL v1.0: Post-Training Library Built to Move with the Field
According to a Quinnipiac University poll, 15% of Americans say they'd be willing to have a job where their direct supervisor was an AI program that assigned tasks and set schedules.
LiteLLM had obtained two security compliance certifications via Delve and fell victim to some horrific credentialstealing malware last week.