Jiaqi Li

The paper presents a lattice-based Ciphertext-Policy Attribute-Based Encryption (CP-ABE) scheme that supports $\mathsf{NC}^1$ access policies while maintaining constant-size ciphertexts.

ClawdGo is a novel framework that provides endogenous security awareness training for autonomous AI agents, enabling them to recognize and reason about internal threats without modifying the underlying model.

Xetrieval introduces an embedding-level framework to mechanistically explain dense retrieval decisions by decomposing high-dimensional embeddings into sparse, human-interpretable features.

The paper introduces SAVE, a framework that uses on-policy feedback and the value function to self-supervise and improve reward models, significantly enhancing RLHF performance across multiple benchmarks.

TempoVLA is a novel Vision-Language-Action model that enables controllable execution speed for robot manipulation by explicitly conditioning the policy on the desired speed.