Pith Number

pith:DIAUVKKU

pith:2026:DIAUVKKU6L2QNJ3U46TTYIW7QH

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Safe-FedLLM: Delving into the Safety of Federated Large Language Models

Mingxiang Tao, Wenxuan Tu, Xiangyan Tang, Xue Yang, Yue Yang, Yu Tian

Safe-FedLLM detects malicious client updates in federated LLM training by classifying distinct patterns in LoRA parameters with lightweight probes.

arxiv:2601.07177 v5 · 2026-01-12 · cs.CR · cs.AI

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Safe-FedLLM effectively improves FedLLM's robustness against malicious clients while maintaining competitive performance on benign data, and remains effective even under high malicious client ratios.

C2weakest assumption

That LoRA updates from malicious clients exhibit reliably distinct behavioral patterns that lightweight classifiers can separate from benign updates without introducing harmful false positives or requiring attack-specific tuning.

C3one line summary

Safe-FedLLM detects malicious client LoRA updates in federated LLM training via step-, client-, and shadow-level probes with lightweight classifiers, improving robustness while preserving benign performance.

Formal links

2 machine-checked theorem links

Cited by

1 paper in Pith

Cloud-native and Distributed Systems for Efficient and Scalable Large Language Models -- A Research Agenda

Receipt and verification

First computed	2026-06-02T01:03:40.642598Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

1a014aa954f2f506a774e7a73c22df81fe4b83001b2fd0c57c0866ee9a558ca6

Aliases

arxiv: 2601.07177 · arxiv_version: 2601.07177v5 · doi: 10.48550/arxiv.2601.07177 · pith_short_12: DIAUVKKU6L2Q · pith_short_16: DIAUVKKU6L2QNJ3U · pith_short_8: DIAUVKKU

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/DIAUVKKU6L2QNJ3U46TTYIW7QH \
  | 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: 1a014aa954f2f506a774e7a73c22df81fe4b83001b2fd0c57c0866ee9a558ca6

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "8ead2f6db993213c21eb1f5236c8143fc1e023b1b9d7329e66ff229bf94e73b3",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CR",
    "submitted_at": "2026-01-12T04:01:03Z",
    "title_canon_sha256": "3d0195cdce21ac69659d64220e660d1496aa211f382002cb4cddb1fe43f1e1d1"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2601.07177",
    "kind": "arxiv",
    "version": 5
  }
}