Fei Huang

The paper introduces ASTRAL, a multimodal LLM-driven framework that reconstructs and analyzes fragmented cyber-physical system architectures to enable comprehensive and quantitative security risk assessment.

MemPrivacy introduces a novel framework that protects sensitive user data in edge-cloud memory systems by replacing private spans with semantically structured placeholders, thereby minimizing data exposure without sacrificing memory utility.

SIRI introduces a self-internalizing reinforcement learning framework that allows LLM agents to autonomously discover and integrate reusable skills directly into their core policy, significantly improving performance on complex tasks without external skill generators.

A multimodal speaker identification system is proposed using Adaptive Modality Routing (AMR) for the POLY-SIM 2026 Grand Challenge, achieving high accuracy in various conditions.

This paper investigates the design of dual-function radar-communication systems for massive MIMO systems using 1-bit DACs and ADCs, optimizing the transmit signal matrix for enhanced sensing performance and communication QoS.

MagicSelector is a framework for tool retrieval in agents using counterfactual task decomposition, progressive reranking, and dynamic Top-K.