arXiv AI
5d ago
Correct Is Not Governed: Provenance Integrity in Agentic Workflows
arXiv:2608. 12761v1 Announce Type: new Abstract: Agentic workflows are commonly evaluated by whether they reach the correct outcome.
Mnemosyne: Agentic Transaction Processing for Validating and Repairing AI-generated Workflows
arXiv:2607. 00269v1 Announce Type: new Abstract: LLMs, solvers, and agent teams increasingly generate workflow actions, repairs, and plans, but a generated action may be syntactically valid yet stale, infeasible, conflicting, or destructive of the evidence that triggered a repair.
Related stories
arXiv AI
Jul 28
MemTX: Transactional Belief Commit for Stateful Agent Memory
arXiv:2607. 23929v1 Announce Type: new Abstract: LLM agents increasingly coordinate through persistent shared memory: one agent's write becomes another agent's premise, and eventually a tool call with real side effects.
arXiv AI
Jul 28
Looping Is Not Reliability: State-Bound Evidence and Typed Revision Contracts for Agentic Code Repair
arXiv:2607. 24604v1 Announce Type: cross Abstract: Generate--test--revise loops are common in coding agents, but repetition alone provides no reliability guarantee.
arXiv AI
Aug 5
GenOS: Compositional Certificates for Semantic Robustness in AI Code Generation
arXiv:2608. 03588v1 Announce Type: cross Abstract: AI coding agents are stochastic workflows: prompts are interpreted, artifacts are sampled, validators produce observations, and orchestrators commit or repair.
arXiv AI
Jul 8
Proof of Execution: Runtime Verification for Governed AI Agent Actions
arXiv:2607. 05397v1 Announce Type: cross Abstract: Agent systems increasingly execute rather than advise.
arXiv Machine Learning
Jun 17
Verified Detection and Prevention of Concurrency Anomalies in Multi-Agent Large Language Model Systems
arXiv:2606. 17182v1 Announce Type: new Abstract: Multi-agent LLM systems share state through memory stores, vector indices, and tool registries.
arXiv AI
Jul 14
Temporary Authority, Permanent Effects: Commit-Time Authorization for LLM Agents
arXiv:2607. 10487v1 Announce Type: cross Abstract: LLM agents can commit durable effects from authority evidence that was valid earlier in execution: a DOM snapshot, approval epoch, version witness, branch token, or worker result.
arXiv AI
Jun 10
Regimes: An Auditable, Held-Out-Gated Improvement Loop Demonstrated on LongMemEval with ActiveGraph
arXiv:2606. 10241v1 Announce Type: new Abstract: Autonomous improvement loops are hard to trust because the improvement process is usually external scaffolding bolted onto the agent: failures go unlogged, diagnoses cannot be replayed, and promote-or-discard decisions land in a side database rather than the agent's own history.
arXiv AI
Jul 29
COVENANT: Natural-Language Workflow Compilation for Aligned Agent Execution
arXiv:2607. 25400v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly entrusted with natural-language workflow instructions (e.
arXiv AI
5d ago
CAPRI: Contract-Aware Proof Repair for Isabelle
arXiv:2608. 13459v1 Announce Type: cross Abstract: We address the use of large language models (LLMs) to help discover Isabelle proofs.
arXiv AI
Jun 30
Always-OnAgents:A Survey of Persistent Memory, State, and Governance in LLMAgents
arXiv:2606. 30306v1 Announce Type: cross Abstract: Always-on agents are systems whose future behavior depends on durable state accumulated across earlier interactions.
arXiv AI
Aug 6
The LLM Proposes, the Executive Disposes: A Self-Verifying Agent Instrument that Dissociates Commitment Drift from Binding Drift in Long-Horizon Agents
arXiv:2608. 04066v1 Announce Type: new Abstract: How do you verify a long-horizon agent when its own state and self-reports are exactly what you cannot trust?