pith:IO25R27P
When Does Multi-Agent Collaboration Help? An Entropy Perspective
Single-agent setups outperform multi-agent LLM collaboration in 43 percent of cases because entropy patterns stabilize after the first round.
arxiv:2602.04234 v6 · 2026-02-04 · cs.MA
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\pithnumber{IO25R27PGJ2BRQSC2ZRSCVUKWQ}
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Claims
a single agent outperforms MAS in approximately 43.3% of cases, and that entropy dynamics are largely determined during the first round of interaction... we introduce a simple yet effective algorithm, the Entropy Judger, to select solutions from MAS's pass@k results, leading to consistent accuracy improvements across all MAS configurations and tasks.
That the 245 entropy features extracted at token, agent, and round levels are sufficient to capture the causal drivers of MAS success or failure without significant confounding from model-specific tokenization or prompt formatting choices.
Entropy patterns show single LLMs often outperform multi-agent groups, first-round dynamics dominate, and an entropy judger improves solution selection across benchmarks.
Receipt and verification
| First computed | 2026-06-05T01:15:19.704519Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
43b5d8ebef327418c242d66321568ab4030d112c0905bcaa1d9c6dee400ebc23
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/IO25R27PGJ2BRQSC2ZRSCVUKWQ \
| 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: 43b5d8ebef327418c242d66321568ab4030d112c0905bcaa1d9c6dee400ebc23
Canonical record JSON
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