Academic Research Support

The design logic, technical feasibility, and performance advantages of the aforementioned PoQ mechanism have been validated through dedicated academic research. For detailed insights, refer to the following papers:

1. Design and Evaluation of Cost-Aware PoQ for Decentralized LLM Inference: Proposes a cost-aware PoQ framework that integrates efficiency metrics into incentive mechanisms. It achieves dynamic balance between quality and cost through a unified evaluation pipeline, verifying the practicality and economic sustainability of the multi-dimensional evaluation system.
2. Optimistic TEE-Rollups: A Hybrid Architecture for Scalable and Verifiable Generative AI Inference on Blockchain: Presents a hybrid verification protocol that provides the underlying architecture for on-chain verifiable proofs. By combining Trusted Execution Environments (TEE) with zero-knowledge spot checks, it resolves the trilemma of verifiability in decentralized inference and further enhances the security and efficiency of PoQ proofs.