MPO
Boosts LLM agents with meta plan optimisation. EMNLP 2025.
At a glance
- Type
- Meta plan optimisation
- Tier
- T3
- Created
- 2025-03 (MPO: Boosting LLM Agents with Meta Plan Optimization; arxiv 2503.02682 submitted March 2025)
- Latest release
- not applicable — not OSS
- License
- not applicable — not OSS
- GitHub
- not applicable — no GitHub repo
- Pricing
- not applicable — not commercial
- Funding
- not applicable — not commercial
Taxonomy
- storage
- vector
- retrieval
- similarity
- persistence
- cross-session
- update
- extraction
- unit
- skill
- governance
- n/a
- conflict
- llm-arbitrate
When to use
Optimised for: not applicable - research paper
Anti-fit: not applicable - research paper
Pros & cons
Pros
Boosts LLM agents with meta plan optimisation — explicit plan-level improvement loop; EMNLP 2025.
Cons
Plan-optimization adds inference cost; quality bounded by base planner.
Claims & capabilities
Meta Plan Optimization framework that incorporates explicit guidance via high-level meta plans, continuously optimized from task execution feedback; plug-and-play solution avoiding retraining for new agents; significantly outperforms baselines on two representative tasks; EMNLP 2025 Findings
Technical surface
- API surface
- not applicable — research paper
- Backend storage
- not applicable — research paper
- Deployment
- not applicable — not a deployable product
- Embedding model
- not applicable — research paper
- Multi-tenancy
- not applicable — research paper
- MCP
- not applicable — research paper, no deployed product
- A2A
- not applicable — research paper, no deployed product
- OpenTelemetry
- not applicable — research paper, no deployed product
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