pith:WGOLOEUS
Robust Agent Compensation (RAC): Teaching AI Agents to Compensate
AI agents can recover from failures using a log-based safety net added through existing framework extensions without rewriting their code.
arxiv:2605.03409 v2 · 2026-05-05 · cs.AI
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\pithnumber{WGOLOEUSJNVKEN5XFPYXL7ZXIW}
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Record completeness
Claims
We present an implementation based on LangChain, demonstrate its viability through the τ-bench and REALM-Bench, and show that when solving complex problems, RAC is 1.5-8X or more better in both latency and token economy compared to state-of-the-art LLM-based recovery approaches.
That the log-based recovery can be implemented via existing extension points without changing current agent code and that it effectively avoids unintended side effects.
RAC adds a log-based safety net to AI agents via framework extensions, delivering 1.5-8X better latency and token use than LLM-based recovery on complex problems in τ-bench and REALM-Bench.
Receipt and verification
| First computed | 2026-05-20T00:04:33.875305Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b19cb712924b6aa237b72bf175ff3745a8b82b86c339a3930063004e9862c366
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/WGOLOEUSJNVKEN5XFPYXL7ZXIW \
| 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: b19cb712924b6aa237b72bf175ff3745a8b82b86c339a3930063004e9862c366
Canonical record JSON
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