Mnemosyne: Agentic Transaction Processing for Validating and Repairing AI-generated Workflows

arXiv:2607.00269 · cs.AI · Submitted 2026-06-30 · Read on arXiv

cs.AI

Submitted: 2026-06-30

Updated: 2026-08-31

Comments: 60 pages, added additional experiments

Code: https://github.com/eyuchang/Mnemosyne

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 51× in this paper · explained in 2 episodes
• Trace — 12× in this paper · explained in 2 episodes
• Agentic Transaction Processing — 8× in this paper
• Provenance — 8× in this paper · explained in 4 episodes
• Consistency — 5× in this paper · explained in 3 episodes
• Regret — 5× in this paper · explained in 3 episodes
• Agentic Workflows — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Failure Modes — 3× in this paper · explained in 3 episodes
• Data Provenance — 2× in this paper · explained in 2 episodes
• Topological Order — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Accountability — 1× in this paper · explained in 2 episodes
• Actor — 1× in this paper · explained in 3 episodes
• Admissibility — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Sycophancy — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Trivium: Temporal Regret as a First-Class Objective for Causal-Memory Controllers
• Reflexion: Language Agents with Verbal Reinforcement Learning
• Voyager: An Open-Ended Embodied Agent with Large Language Models
• A Survey on Large Language Model based Autonomous Agents
• Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models

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