pith:NUOAWJTF
Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive
Standard DPO can lower the absolute likelihood of preferred responses while still raising their relative odds; a modified loss called DPOP prevents the drop and improves results.
arxiv:2402.13228 v2 · 2024-02-20 · cs.CL · cs.AI · cs.LG
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Claims
we find that DPOP outperforms DPO and other fine-tuning procedures across a wide variety of datasets and downstream tasks, including datasets with high edit distances between completions. Furthermore, we find that the DPOP-tuned model outperforms the DPO-tuned model (all else equal) on benchmarks independent of the fine-tuning data, such as MT-Bench. Finally, using DPOP, we create and open-source Smaug-34B and Smaug-72B, with the latter becoming the first open-source LLM to surpass an average accuracy of 80% on the HuggingFace Open LLM Leaderboard.
That the identified DPO failure mode is the primary limiter of performance and that the DPOP modification will generalize without introducing new unintended effects on model behavior or other tasks.
DPOP is a new loss function that prevents DPO from lowering preferred response likelihoods and outperforms standard DPO on diverse datasets, MT-Bench, and enables Smaug-72B to exceed 80% on the Open LLM Leaderboard.
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| First computed | 2026-05-17T23:38:12.705233Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519 (pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
6d1c0b2665de3792d4c940131711a151ec0949739234f6c31e62289f1583e999
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/NUOAWJTF3Y3ZFVGJIAJROENBKH \
| jq -c '.canonical_record' \
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Canonical record JSON
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