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pith:JPSMKDCK

pith:2025:JPSMKDCKL4R2ODSQMYZPR2DOLQ
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DGS-Net: Distillation-Guided Gradient Surgery for CLIP Fine-Tuning in AI-Generated Image Detection

Boyu Wang, Fan Wang, Jiazhen Yan, Zhangjie Fu, Ziqiang Li, Ziwen He

By projecting task gradients onto the orthogonal complement of harmful directions and aligning with beneficial ones distilled from a frozen CLIP encoder, DGS-Net fine-tunes for AI-generated image detection without catastrophic forgetting.

arxiv:2511.13108 v4 · 2025-11-17 · cs.CV

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Claims

C1strongest claim

By projecting task gradients onto the orthogonal complement of harmful directions and aligning with beneficial ones distilled from a frozen CLIP encoder, DGS-Net achieves unified optimization of prior preservation and irrelevant suppression, outperforming state-of-the-art approaches by an average margin of 6.6% across 50 generative models.

C2weakest assumption

That the proposed gradient-space decomposition can reliably and consistently separate harmful from beneficial descent directions without introducing instability or requiring extensive hyperparameter tuning specific to each dataset.

C3one line summary

DGS-Net applies distillation-guided gradient surgery during CLIP fine-tuning to preserve pre-trained knowledge and suppress irrelevant features, reporting 6.6% average gains over prior methods on 50 generative models.

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First computed 2026-05-20T00:01:37.038776Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

4be4c50c4a5f23a70e506632f8e86e5c37e99067b3615799171250c76b69623a

Aliases

arxiv: 2511.13108 · arxiv_version: 2511.13108v4 · doi: 10.48550/arxiv.2511.13108 · pith_short_12: JPSMKDCKL4R2 · pith_short_16: JPSMKDCKL4R2ODSQ · pith_short_8: JPSMKDCK
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/JPSMKDCKL4R2ODSQMYZPR2DOLQ \
  | 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())"
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Canonical record JSON
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