pith:DCYCOXIS
LLM4Log: A Systematic Review of Large Language Model-based Log Analysis
A review of 145 papers maps LLM use across seven log analysis tasks and distills patterns plus adoption challenges.
arxiv:2604.16359 v2 · 2026-03-18 · cs.SE
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\usepackage{pith}
\pithnumber{DCYCOXISIG4NILJFYE7D7COQZL}
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Record completeness
Claims
Following a structured search and manual screening protocol, we completed literature collection in November 2025 and identified 145 unique papers across seven logging tasks. We synthesize the research area through a unified, task-driven taxonomy, summarize common design patterns, and distill key lessons and open challenges for reliable real-world adoption.
The structured search protocol and manual screening captured a representative and unbiased sample of all relevant LLM-based log analysis papers published up to November 2025.
LLM4Log is a systematic review of 145 papers on LLM-based log analysis that delivers a unified taxonomy, design patterns, and open challenges for reliable adoption in AIOps.
Receipt and verification
| First computed | 2026-05-21T01:04:25.866618Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
18b0275d1241b8d42d25c13e3f89d0cae0b6124a544e359d72becd95a60b0a02
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/DCYCOXISIG4NILJFYE7D7COQZL \
| 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: 18b0275d1241b8d42d25c13e3f89d0cae0b6124a544e359d72becd95a60b0a02
Canonical record JSON
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