pith:FPSK2ACZ
LightTune: Lightweight Forward-Only Online Fine-Tuning with Applications to Link Adaptation
LightTune provides a backpropagation-free online fine-tuning method that adapts ML models on mobile devices to new conditions by triggering forward-only updates only when performance drops below a threshold.
arxiv:2604.12406 v2 · 2026-04-14 · cs.NI
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Claims
LightTune, a lightweight, backpropagation-free online fine-tuning framework with provable convergence guarantees, enables a substantial reduction in the average BLER prediction error of up to 48.8% and average throughput improvements of up to 15.5% compared to conventional OLLA.
That opportunistically triggering fine-tuning only when performance falls below a predefined threshold, combined with forward-only updates, is sufficient to achieve reliable adaptation and convergence under real-world distributional shifts without introducing instability or excessive overhead.
LightTune introduces a lightweight forward-only online fine-tuning framework that reduces BLER prediction error by up to 48.8% and boosts throughput by 15.5% in 6G link adaptation.
Receipt and verification
| First computed | 2026-05-22T01:04:02.234604Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
2be4ad0059ef1651813e055b2d739790373aacede0197ae3221fe916cb82b8d1
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/FPSK2ACZ54LFDAJ6AVNS244XSA \
| 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: 2be4ad0059ef1651813e055b2d739790373aacede0197ae3221fe916cb82b8d1
Canonical record JSON
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