pith:2YFA7KKG
InvEvolve: Evolving White-Box Inventory Policies via Large Language Models with Performance Guarantees
InvEvolve uses large language models to evolve white-box inventory policies with statistical safety guarantees and a lower bound on success probability.
arxiv:2605.00369 v4 · 2026-05-01 · cs.LG · cs.AI
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\pithnumber{2YFA7KKGV5SEELUIW7TBFX5ZMB}
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Record completeness
Claims
InvEvolve evolves new policies that improve upon existing benchmarks and provides a lower bound on the probability that it evolves a statistically safe and improved policy, with outperformance shown on both synthetic data and real-world retail data.
The unified theoretical model correctly connects training, inference, and deployment to deliver a valid lower bound on the probability of a safe improved policy and an accurate characterization of the multi-period performance gap relative to the oracle-safe benchmark.
InvEvolve evolves white-box inventory policies from LLMs with statistical safety guarantees and outperforms classical and deep learning methods on synthetic and real retail data.
Formal links
Receipt and verification
| First computed | 2026-06-08T01:04:06.180445Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
d60a0fa946af64422e88b7e612dfb9605f38cfcd4023e999f9e747f2c8d5ad79
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/2YFA7KKGV5SEELUIW7TBFX5ZMB \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: d60a0fa946af64422e88b7e612dfb9605f38cfcd4023e999f9e747f2c8d5ad79
Canonical record JSON
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