This paper introduces a systems-level conceptual framing and a three-level taxonomy (intra-model, system-level, socio-technical) for uncertainty propagation in compound LLM applications, along with engineering insights and open challenges.
arXiv preprint arXiv:2508.07935 , year=
4 Pith papers cite this work. Polarity classification is still indexing.
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Introduces EPC-AW to mitigate epistemic miscalibration in LLM multi-agent planning via consistency-based selection and refinement, reporting 9.75% average success improvement.
The paper proposes a unified MDP-based research agenda for addressing sim-to-real gaps in foundation model agents and advocates adopting classical solutions such as domain randomization.
This survey categorizes anomalies in agent systems into intra-agent and inter-agent types and introduces the AgentOps framework with four operational stages.
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Uncertainty Propagation in LLM-Based Systems
This paper introduces a systems-level conceptual framing and a three-level taxonomy (intra-model, system-level, socio-technical) for uncertainty propagation in compound LLM applications, along with engineering insights and open challenges.
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When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systems
Introduces EPC-AW to mitigate epistemic miscalibration in LLM multi-agent planning via consistency-based selection and refinement, reporting 9.75% average success improvement.
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The Sim-to-Real Gap of Foundation Model Agents: A Unified MDP Perspective
The paper proposes a unified MDP-based research agenda for addressing sim-to-real gaps in foundation model agents and advocates adopting classical solutions such as domain randomization.
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Agent System Operations: Categorization, Challenges, and Future Directions
This survey categorizes anomalies in agent systems into intra-agent and inter-agent types and introduces the AgentOps framework with four operational stages.