pith:NZPDVXNX
MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI
AI agents cannot reliably invent ML methods that beat human designs on generalization and scaling tests.
arxiv:2605.08678 v2 · 2026-05-09 · cs.LG
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\pithnumber{NZPDVXNXRUX6HU5FEAADKKJ2BB}
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Record completeness
Claims
Current agents remain far from reliably surpassing human-designed methods, and that engineering-style tuning is easier for them than genuine method invention.
The 140 tasks and 12 domains sufficiently capture the core skills needed for inventing generalizable and scalable ML methods without missing key aspects of real research.
MLS-Bench shows that current AI agents fall short of reliably inventing generalizable ML methods, with engineering tuning easier than genuine invention.
Receipt and verification
| First computed | 2026-05-28T01:04:41.928394Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
6e5e3addb78d2fe3d3a5200035293a086f16fa3ee433f15379a80521a3e76351
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/NZPDVXNXRUX6HU5FEAADKKJ2BB \
| 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: 6e5e3addb78d2fe3d3a5200035293a086f16fa3ee433f15379a80521a3e76351
Canonical record JSON
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