Persistent and Conversational Multi-Method Explainability for Trustworthy Financ
arXiv:2604.22748v1 Announce Type: new Abstract: As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment
arXiv:2609.20989v2 Announce Type: cross Abstract: As generative AI is increasingly used as a source of personal financial guidance, understanding how people appraise such advice
arXiv:2605.11595v1 Announce Type: new Abstract: The EU Artificial Intelligence Act (Regulation 2024/1689), fully applicable to high-risk systems from August 2026, creates urgent
arXiv:2603.18028v1 Announce Type: cross Abstract: While explainable AI (XAI) is often heralded as a means to enhance transparency and trustworthiness in closed-loop
arXiv:2604.15898v1 Announce Type: new Abstract: For around a decade, non-symbolic methods have been the option of choice when explaining complex machine learning (ML) models.
arXiv:2605.21758v1 Announce Type: new Abstract: Explainable AI (XAI) methods identify which features are relevant to a model's predictions but often fail to clarify why certain
arXiv:2604.15371v1 Announce Type: cross Abstract: Large language models (LLMs) achieve strong performance across many natural language processing tasks, yet their decision
arXiv:2604.08590v1 Announce Type: cross Abstract: We present AlphaLab, an autonomous research harness that leverages frontier LLM agentic capabilities to automate the full
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