Beyond Corrected Memory: Execution Consistency in Multi-Agent Systems
cs.AI
Submitted: 2026-10-06
Updated: 2026-10-06
Comments: 39 pages, 7 figures, 30 tables (including appendix)
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- AgentRx: Diagnosing AI Agent Failures from Execution Trajectories
- $\tau^2$-Bench: Evaluating Conversational Agents in a Dual-Control Environment
- Beyond Task Completion: Revealing Corrupt Success in LLM Agents through Procedure-Aware Evaluation
- Seeing the Whole Elephant: A Benchmark for Failure Attribution in LLM-based Multi-Agent Systems
- LongCLI-Bench: A Preliminary Benchmark and Study for Long-horizon Agentic Programming in Command-Line Interfaces
- Verified Detection and Prevention of Concurrency Anomalies in Multi-Agent Large Language Model Systems
- Multi-Agent Transactive Memory
- MemTX: Transactional Belief Commit for Stateful Agent Memory
- MECoBench: A Systematic Study of Multimodal Agent Collaboration in Embodied Environments
- Dealing with observability in interaction-based Offline Runtime Verification of Distributed Systems
- Governed Shared Memory for Multi-Agent LLM Systems
- GateMem: Benchmarking Memory Governance in Multi-Principal Shared-Memory Agents
- CoffeeBench: Benchmarking Long-Horizon LLM Agents in Heterogeneous Multi-Agent Economies
- StateFuse: Deterministic Conflict-Preserving Memory for Multi-Agent Systems
- TOKI: A Bitemporal Operator Algebra for Contradiction Resolution in LLM-Agent Persistent Memory
- PAST-Bench: Benchmarking the Foundations of Recursive Self-Improvement in Personal Agents
- Beyond the All-in-One Agent: Benchmarking Role-Specialized Multi-Agent Collaboration in Enterprise Workflows
- Multi-Agent Memory from a Computer Architecture Perspective: Visions and Challenges Ahead
- AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems
- AgentWebBench: Benchmarking Multi-Agent Coordination in Agentic Web
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems