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Reppo’s curation mechanism is stake-assured human feedback (SAHF). Rather than granting curation influence based on time spent or engagement metrics, Reppo requires voters to lock REPPO tokens to obtain veREPPO — their voting authority — and then allocate that authority across datanets and pods each epoch. Economic risk backs every quality signal the network produces.

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Voting power formula

Your voting power is determined by two factors:
  • Amount locked — more REPPO locked yields more veREPPO
  • Lock duration — longer commitments yield more voting power per token
REPPO locked × lock duration → veREPPO (voting power)
Splitting tokens across multiple wallets does not multiply voting power. Because voting weight scales with capital locked, Sybil attacks — creating many accounts to dilute or manipulate curation — are economically self-defeating.

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How votes work each epoch

Each epoch runs for 48 hours. During that window:
1

Distribute voting power across datanets

veREPPO holders allocate their total voting power across the datanets they want to participate in. You can split across multiple datanets in any proportion.
2

Allocate within datanets to specific pods

Within each datanet, you allocate your share of voting power toward specific pods — casting votes for or against based on your quality assessment.
3

Time decay applies

Voting power decays linearly throughout the epoch. A vote cast at the start of the epoch carries more weight than the same vote cast near the end.
4

Two-sided voting creates adversarial pressure

Any participant can vote against a pod. This means artificial support for low-quality content can be directly challenged, and bribery schemes become ongoing capital contests rather than one-time payments.
5

Epoch closes and tallies determine rewards

At epoch end, net vote tallies across all pods determine how emissions are distributed to publishers and how curation accuracy scores are calculated for voters.

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Time decay

Earlier votes carry more weight. A voter who identifies a high-quality submission early in the epoch earns more than one who casts the same vote near the close. This design discourages vote sniping — waiting to see which way consensus is forming before piling on — and rewards genuine conviction.

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Two-sided voting

Votes can be cast for or against any pod. This means:
  • Artificial inflation of a low-quality pod’s score can be directly countered
  • Supporting a pod through bribery requires maintaining that capital commitment every epoch as opponents can challenge it
  • Markets self-correct through continuous adversarial pressure rather than relying on manual moderation

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Adversarial robustness

The voting design addresses common manipulation vectors systematically:
Attack vectorDefense mechanism
Spam submissionsPay-to-publish requires upfront REPPO capital per pod
Sybil votingStake-weighted: splitting capital across accounts reduces total influence
Artificial supportTwo-sided voting: any participant can challenge any position directly
Vote snipingTime decay: earlier signals receive higher weight
Coordination attacksContinuous repricing: positions respond in real time as capital moves

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Curation signals as training data

Every action on Reppo — submissions, votes, rankings, and written feedback — produces structured preference signals. These signals are the network’s primary output. AI teams access not just curated content but the preference signal itself: ordered comparisons, for/against labels, and written rationales suitable for RLHF (reinforcement learning from human feedback) and DPO (direct preference optimization) training pipelines.
Vote feedback submitted via POST /feedback/pods/{id} attaches structured written rationale to a vote. This adds qualitative signal on top of the quantitative veREPPO weight, enriching the training data that flows downstream.