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pith:Z3NS6PQ4

pith:2026:Z3NS6PQ4EMUPIP33DE3W6SNWSY

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Reducing Bias and Variance: Generative Semantic Guidance and Bi-Layer Ensemble for Image Clustering

Feijiang Li, Jieting Wang, Liang Du, Saixiong Liu, Zhenxiong Li, Zizheng Jiu

GSEC generates adaptive semantic descriptions with multimodal LLMs and applies a bi-layer ensemble to reduce both bias and variance in image clustering.

arxiv:2605.12961 v1 · 2026-05-13 · cs.CV · cs.LG

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Claims

C1strongest claim

Comparative experiments demonstrate that GSEC outperforms 18 state-of-the-art methods across six benchmark datasets, while further analysis confirms its effectiveness in simultaneously reducing both bias and variance.

C2weakest assumption

That semantic descriptions generated by current multimodal LLMs supply unbiased, task-adaptive prior knowledge that improves clustering more reliably than matching against predefined vocabularies, and that the bi-layer ensemble reduces variance without introducing new systematic errors.

C3one line summary

GSEC uses MLLM-generated semantic guidance and bi-layer ensemble learning to reduce bias and variance, outperforming 18 prior methods on six image clustering benchmarks.

References

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[1] Food-101–mining discriminative com- ponents with random forests 2014

[2] Bagging predictors.Machine learning, 24(2):123–140, 1996

[3] Random forests.Machine learning, 45(1):5–32, 2001

[4] Semantic-enhanced im- age clustering 2023

[5] Deep clustering for unsupervised learning of visual features 2018

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Receipt and verification

First computed	2026-05-18T03:09:09.162903Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

cedb2f3e1c2328f43f7b19376f49b69638538b2e8c7f5ee3c0aef7fd71355f47

Aliases

arxiv: 2605.12961 · arxiv_version: 2605.12961v1 · doi: 10.48550/arxiv.2605.12961 · pith_short_12: Z3NS6PQ4EMUP · pith_short_16: Z3NS6PQ4EMUPIP33 · pith_short_8: Z3NS6PQ4

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curl -sH 'Accept: application/ld+json' https://pith.science/pith/Z3NS6PQ4EMUPIP33DE3W6SNWSY \
  | 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: cedb2f3e1c2328f43f7b19376f49b69638538b2e8c7f5ee3c0aef7fd71355f47

Canonical record JSON

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    "license": "http://creativecommons.org/licenses/by/4.0/",
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