Artemis: Toward Accurate Detection of Server-Side Request Forgeries through LLM-Assisted Inter-procedural Path-Sensitive Taint Analysis.
Proc. ACM Program. Lang., 2025
Enabling collaborative assembly between humans and robots using a digital twin system.
Robotics Comput. Integr. Manuf., April, 2024
Fine-detailed Neural Indoor Scene Reconstruction using multi-level importance sampling and multi-view consistency.
CoRR, 2024
A Large Language Model-based multi-agent manufacturing system for intelligent shopfloor.
CoRR, 2024
Efficient Algorithms for Top-k Stabbing Queries on Weighted Interval Data (Full Version).
CoRR, 2024
We Choose to Go to Space: Agent-driven Human and Multi-Robot Collaboration in Microgravity.
CoRR, 2024
Fine-Detailed Neural Indoor Scene Reconstruction Using Multi-Level Importance Sampling And Multi-View Consistency.
Proceedings of the IEEE International Conference on Image Processing, 2024
SAFE: Sampling-Assisted Fast Learned Cardinality Estimation for Dynamic Spatial Data.
Proceedings of the Database and Expert Systems Applications, 2024
Efficient Algorithms for Top-k Stabbing Queries on Weighted Interval Data.
Proceedings of the Database and Expert Systems Applications, 2024
Poster: Whether We Are Good Enough to Detect Server-Side Request Forgeries in PHP-native Applications?
Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, 2024
Critique of "A Parallel Framework for Constraint-Based Bayesian Network Learning via Markov Blanket Discovery" by SCC Team From ShanghaiTech University.
IEEE Trans. Parallel Distributed Syst., June, 2023
A Multimodal Construction Method for a Digital Twin System with Human-Robot Collaboration.
Proceedings of the 8th International Conference on Control, Robotics and Cybernetics, 2023
An Improved Packet Head Detection Method in Massive Access.
Proceedings of the 95th IEEE Vehicular Technology Conference, 2022
A Performance Study of One-dimensional Learned Cardinality Estimation.
Proceedings of the 24th International Workshop on Design, 2022