He Chen

The paper proposes SemBugger, a polymorphic backdoor attack that uses intensity-based poisoning to achieve diverse malicious outcomes in Semantic Communication (SC) systems, alongside a provable defense mechanism.

GEO-Bench introduces a standardized benchmark to compare various ranking manipulation attacks (both black-box and white-box) on generative engines, demonstrating that black-box content rewriting can be highly effective and stealthy.

The paper introduces GEO-Bench, a unified benchmark that standardizes the evaluation of various generative engine optimization (GEO) ranking manipulation attacks, demonstrating that black-box content rewriting can be highly effective and stealthy compared to gradient-based methods.

Qwen-VLA introduces a unified embodied foundation model that extends vision-language understanding to continuous action generation, enabling robust, multi-task generalization across diverse robotic tasks and embodiments.

This paper introduces Numca and Hista, two novel techniques that significantly improve state value estimation for LLM reinforcement learning, addressing the instability of standard critic approaches.

The paper proposes GUIDE, a physics-guided deep unfolding framework that enables practical, real-time cross-band channel prediction for AI-RAN by embedding wireless channel physics, significantly improving beamforming gain while maintaining high inference speed.