mlsanityData to 7 Oct 2026

Agentic AI, Retrieval-Augmented Generation, and the Institutional Turn: Legal Architectures and Financial Governance in the Age of Distributional AGI

arXiv 2603.13244 ↗First posted 20 Feb 2026cs.CY cs.AI cs.CEcited by 0

On the map: LLM agents and tool use → Financial trading and forecasting agents

Abstract (arXiv)

The proliferation of agentic artificial intelligence systems--characterized by autonomous goal-seeking, tool use, and multi-agent coordination--presents unprecedented challenges to existing legal and financial regulatory frameworks. While traditional AI governance has focused on model-level alignment through training-time interventions such as Reinforcement Learning from Human Feedback (RLHF), the deployment of large language models (LLMs) as persistent agents necessitates a paradigm shift toward institutional governance structures. This paper examines the intersection of agentic AI, Retrieval-Augmented Generation (RAG), and their implications for legal accountability and financial market integrity. Through analysis of the Institutional AI framework, we argue that alignment must be reconceptualized as a mechanism design problem involving runtime governance graphs, sanction functions, and observable behavioral constraints rather than internalized constitutional values[...].The analysis concludes that the future of AI governance lies not in perfecting isolated model behavior, but in architecting institutional environments where compliant behavior emerges as the dominant strategy through carefully calibrated payoff landscapes.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 28 of its 46 references that are in the map. First posted on arXiv 20 Feb 2026.

Builds on

28 of 46 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024Strategic Collusion of LLM Agents: Market Division in Multi-Commodity Competitions19 Sep

Other references · 27

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  2. 2022Emergent Abilities of Large Language Modelscited by 2,483
  3. 2024Frontier Models are Capable of In-context Schemingcited by 252
  4. 2019Risks from Learned Optimization in Advanced Machine Learning Systemscited by 250
  5. 2022The Alignment Problem from a Deep Learning Perspectivecited by 246
  6. 2025Agentic Misalignment: How LLMs Could Be Insider Threatscited by 136
  7. 2025Towards a Science of Scaling Agent Systemscited by 125
  8. 2021Goal Misgeneralization in Deep Reinforcement Learningcited by 122
  9. 2019Optimal Policies Tend to Seek Powercited by 115
  10. 2025SycEval: Evaluating LLM Sycophancycited by 101
  11. 2024Sycophancy in Large Language Models: Causes and Mitigationscited by 97
  12. 2021Consequences of Misaligned AIcited by 79
15 more
  1. 2024From Yes-Men to Truth-Tellers: Addressing Sycophancy in Large Language Models with Pinpoint Tuningcited by 51
  2. 2025Inference-Time Reward Hacking in Large Language Modelscited by 32
  3. 2023The Moral Machine Experiment on Large Language Modelscited by 24
  4. 2025Emergent Coordination in Multi-Agent Language Modelscited by 22
  5. 2025Training language models to be warm and empathetic makes them less reliable and more sycophanticcited by 19
  6. 2025Sycophancy under Pressure: Evaluating and Mitigating Sycophantic Bias via Adversarial Dialogues in Scientific QAcited by 16
  7. 2025The Steganographic Potentials of Language Modelscited by 10
  8. 2024Large-scale moral machine experiment on large language modelscited by 9
  9. 2025When Autonomy Goes Rogue: Preparing for Risks of Multi-Agent Collusion in Social Systemscited by 9
  10. 2023A Review of the Evidence for Existential Risk from AI via Misaligned Power-Seekingcited by 7
  11. 2024Roadmap on Incentive Compatibility for AI Alignment and Governance in Sociotechnical Systemscited by 6
  12. 2025Scheming Ability in LLM-to-LLM Strategic Interactionscited by 4
  13. 2026Towards AGI A Pragmatic Approach Towards Self Evolving Agentcited by 2
  14. 2022Understanding Emergent Behaviours in Multi-Agent Systems with Evolutionary Game Theorycited by 1
  15. 2026What is the AGI in Offensive Security ?cited by 1

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