Multi-agent LLM systems are increasingly deployed

The gap

Evidence profile

Stated in the abstract and cells research gap and cells future research sections of the source papers, classified as general, spanning 3 journals.

Supporting evidence — 4 representative gaps

• Failure Propagation and Self-Correction in Multi-Agent LLM Systems: How Deliberative Consensus, Credit Assignment, and Architectural Isolation Jointly Determine Systemic Reliability (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi

  Multi-agent LLM systems are increasingly deployed in settings where individual agent failures can cascade across the collective, yet the mechanisms by which such failures propagate—and the structural conditions under which they are contained or corrected—remain poorly characterized.

  generalstated in abstractevidence 5/5
  Keywords: agent failures multi systems increasingly deployed settings individual cascade across collective mechanisms propagate structural conditions
• A Framework for Evaluating Agentic Skills at Scale (2026) · arXiv

  Agent skills -- structured, reusable knowledge artifacts that augment LLM agent capabilities -- have been rapidly adopted in industry, yet their cross-domain impact and use across commercial and open-source models remain under-studied, and no reusable methodology exists for evaluating an individual skill.

  generalstated in abstractevidence 5/5
  Keywords: agent reusable skills structured knowledge artifacts augment capabilities rapidly adopted industry cross domain impact across
• Exploring Large Language Model‐Based Intelligent Agents: Definitions, Methods, and Prospects (2026) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi

  The paper identifies a gap in the current research on LLM-based agents, particularly in terms of their potential applications and challenges. - It notes that current research is still far from achieving artificial general intelligence. - The paper identifies a need for further research on the development of more sophisticated and effective LLM-based agents.

  generalstated in cells research gapevidence 5/5
  Keywords: paper identifies gap current research llm-based agents particularly
• Exploring Large Language Model‐Based Intelligent Agents: Definitions, Methods, and Prospects (2026) · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · doi

  The paper suggests that future research should focus on addressing the challenges faced by LLM-based agents, such as LLM's inherent limitations, dynamic expansion of MAS, and security and trust issues. - It proposes that future research should explore the potential applications of LLM-based agents in various fields. - The paper suggests that future research should aim to develop more sophisticated and effective LLM-based agents.

  generalstated in cells future researchevidence 5/5
  Keywords: paper suggests future research focus addressing challenges faced

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