We propose DictPFL, a framework that ensures efficient and private federated learning (FL) by encrypting shared gradients and keeping most gradients local, while still preserving the performance of global gradient aggregation.

Current AI benchmarks suffer from systematic flaws like data leakage and selective reporting. We propose PeerBench, a community-run eval platform with secret and live tests and reputation-weighted scoring to restore trust in AI performance claims.