QoS-aware long-term based service composition in cloud computing. - Shengcai Liu; Yufan Wei; Ke Tang 001; A. Kai Qin; Xin Yao 001 (CEC, 2015)

ℓ1/2, 1 group sparse regularization for compressive sensing. - Shengcai Liu; Jiang-She Zhang 001; Junmin Liu; Qingyan Yin (Signal Image Video Process., 2016)

Experience-based Optimization: A Coevolutionary Approach. - Shengcai Liu; Ke Tang 001; Xin Yao 001 (CoRR, 2017)

Automatic Construction of Parallel Portfolios via Explicit Instance Grouping. - Shengcai Liu; Ke Tang 001; Xin Yao 001 (AAAI, 2019)

On Performance Estimation in Automatic Algorithm Configuration. - Shengcai Liu; Ke Tang 001; Yunwen Lei; Xin Yao 001 (AAAI, 2020)

Leveraging TSP Solver Complementarity via Deep Learning. - Kangfei Zhao; Shengcai Liu; Yu Rong 001; Jeffrey Xu Yu (CoRR, 2020)

Few-shots Parameter Tuning via Co-evolution. - Ke Tang 001; Shengcai Liu; Peng Yang 008; Xin Yao 001 (CoRR, 2020)

Towards Feature-free TSP Solver Selection: A Deep Learning Approach. - Kangfei Zhao; Shengcai Liu; Jeffrey Xu Yu; Yu Rong 001 (IJCNN, 2021)

A New Knowledge Gradient-based Method for Constrained Bayesian Optimization. - Wenjie Chen; Shengcai Liu; Ke Tang 001 (CoRR, 2021)

HydraText: Multi-objective Optimization for Adversarial Textual Attack. - Shengcai Liu; Ning Lu 006; Cheng Chen; Chao Qian 001; Ke Tang 001 (CoRR, 2021)

A heuristic repair method for dial-a-ride problem in intracity logistic based on neighborhood shrinking. - Minshi Chen; Jianxun Chen; Peng Yang 008; Shengcai Liu; Ke Tang 001 (Multim. Tools Appl., 2021)

Memetic search for vehicle routing with simultaneous pickup-delivery and time windows. - Shengcai Liu; Ke Tang 001; Xin Yao 001 (Swarm Evol. Comput., 2021)

Few-Shots Parallel Algorithm Portfolio Construction via Co-Evolution. - Ke Tang 001; Shengcai Liu; Peng Yang 008; Xin Yao 001 (IEEE Trans. Evol. Comput., 2021)

Disentangled Contrastive Learning for Social Recommendation. - Jiahao Wu 004; Wenqi Fan; Jingfan Chen; Shengcai Liu; Qing Li 001; Ke Tang 001 (CIKM, 2022)

Training Quantized Deep Neural Networks via Cooperative Coevolution. - Fu Peng; Shengcai Liu; Ning Lu 006; Ke Tang 001 (ICSI (2), 2022)

How Good Is Neural Combinatorial Optimization? - Shengcai Liu; Yu Zhang 111; Ke Tang 001; Xin Yao 001 (CoRR, 2022)

Automatic Construction of Parallel Algorithm Portfolios for Multi-objective Optimization. - Xiasheng Ma; Shengcai Liu; Wenjing Hong (CoRR, 2022)

Efficient Combinatorial Optimization for Word-Level Adversarial Textual Attack. - Shengcai Liu; Ning Lu 006; Cheng Chen; Ke Tang 001 (IEEE ACM Trans. Audio Speech Lang. Process., 2022)

Generative Adversarial Construction of Parallel Portfolios. - Shengcai Liu; Ke Tang 001; Xin Yao 001 (IEEE Trans. Cybern., 2022)

Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles. - Shengcai Liu; Fu Peng; Ke Tang 001 (AAAI, 2023)

A Sample Reuse Strategy for Dynamic Influence Maximization Problem. - Shaofeng Zhang; Shengcai Liu; Ke Tang 001 (BIC-TA (2), 2023)

Multi-Domain Learning from Insufficient Annotations. - Rui He; Shengcai Liu; Jiahao Wu 004; Shan He 001; Ke Tang 001 (ECAI, 2023)

Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend. - Ning Lu 006; Shengcai Liu; Zhirui Zhang; Qi Wang; Haifeng Liu; Ke Tang 001 (CoRR, 2023)

Large Language Models can be Guided to Evade AI-Generated Text Detection. - Ning Lu 006; Shengcai Liu; Rui He; Qi Wang; Ke Tang 001 (CoRR, 2023)

Data-Driven Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and Applications. - Xuanfeng Li; Shengcai Liu; Jin Wang 024; Xiao Chen; Yew-Soon Ong; Ke Tang 001 (CoRR, 2023)

Neural Influence Estimator: Towards Real-time Solutions to Influence Blocking Maximization. - Wenjie Chen; Shengcai Liu; Yew-Soon Ong; Ke Tang 001 (CoRR, 2023)

Enhancing Graph Collaborative Filtering via Uniformly Co-Clustered Intent Modeling. - Jiahao Wu 004; Wenqi Fan; Shengcai Liu; Qijiong Liu; Qing Li 001; Ke Tang 001 (CoRR, 2023)

Dataset Condensation for Recommendation. - Jiahao Wu 004; Wenqi Fan; Shengcai Liu; Qijiong Liu; Rui He; Qing Li 001; Ke Tang 001 (CoRR, 2023)

Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation. - Jiahao Wu 004; Qijiong Liu; Hengchang Hu; Wenqi Fan; Shengcai Liu; Qing Li 001; Xiao-Ming Wu 003; Ke Tang 001 (CoRR, 2023)

Pointer Networks Trained Better via Evolutionary Algorithms. - Muyao Zhong; Shengcai Liu; Bingdong Li; Haobo Fu; Ke Tang 001; Peng Yang 008 (CoRR, 2023)

Saliency Attack: Towards Imperceptible Black-box Adversarial Attack. - Zeyu Dai 001; Shengcai Liu; Qing Li 001; Ke Tang 001 (ACM Trans. Intell. Syst. Technol., 2023)

Multi-Domain Active Learning: Literature Review and Comparative Study. - Rui He; Shengcai Liu; Shan He 001; Ke Tang 001 (IEEE Trans. Emerg. Top. Comput. Intell., 2023)

How Good is Neural Combinatorial Optimization? A Systematic Evaluation on the Traveling Salesman Problem. - Shengcai Liu; Yu Zhang 111; Ke Tang 001; Xin Yao 001 (IEEE Comput. Intell. Mag., 2023)

A Population Cooperation based Particle Swarm Optimization algorithm for large-scale multi-objective optimization. - Yongfan Lu; Bingdong Li; Shengcai Liu; Aimin Zhou (Swarm Evol. Comput., 2023)

Large Language Models as Evolutionary Optimizers. - Shengcai Liu; Caishun Chen; Xinghua Qu; Ke Tang 001; Yew-Soon Ong (CEC, 2024)

Towards Geometry-Aware Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization. - Yongfan Lu; Zixiang Di; Bingdong Li; Shengcai Liu; Hong Qian; Peng Yang 008; Ke Tang 001; Aimin Zhou (CoRR, 2024)

Learning Mixture-of-Experts for General-Purpose Black-Box Discrete Optimization. - Shengcai Liu; Zhiyuan Wang; Yew-Soon Ong; Xin Yao 001; Ke Tang 001 (CoRR, 2024)

Backdoor Graph Condensation. - Jiahao Wu 004; Ning Lu 006; Zeiyu Dai; Wenqi Fan; Shengcai Liu; Qing Li 001; Ke Tang 001 (CoRR, 2024)

Hybrid Memetic Search for Electric Vehicle Routing with Time Windows, Simultaneous Pickup-Delivery, and Partial Recharges. - Zubin Zheng; Shengcai Liu; Yew-Soon Ong (CoRR, 2024)

Datastore Distillation for Nearest Neighbor Machine Translation. - Yuhan Dai; Zhirui Zhang; Yichao Du; Shengcai Liu; Lemao Liu; Tong Xu 001 (IEEE ACM Trans. Audio Speech Lang. Process., 2024)

Large Language Models can be Guided to Evade AI-generated Text Detection. - Ning Lu 006; Shengcai Liu; Rui He; Yew-Soon Ong; Qi Wang; Ke Tang 001 (Trans. Mach. Learn. Res., 2024)

Effective and Imperceptible Adversarial Textual Attack Via Multi-objectivization. - Shengcai Liu; Ning Lu 006; Wenjing Hong; Chao Qian 001; Ke Tang 001 (ACM Trans. Evol. Learn. Optim., 2024)

Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and Applications. - Xuanfeng Li; Shengcai Liu; Jin Wang 024; Xiao Chen; Yew-Soon Ong; Ke Tang 001 (IEEE Trans. Cybern., 2024)

Condensing Pre-Augmented Recommendation Data via Lightweight Policy Gradient Estimation (Extended Abstract). - Jiahao Wu 004; Wenqi Fan; Jingfan Chen; Shengcai Liu; Qijiong Liu; Rui He; Qing Li 001; Ke Tang 001 (ICDE, 2025)

Backdoor Graph Condensation. - Jiahao Wu 004; Ning Lu 006; Zeyu Dai 001; Kun Wang 056; Wenqi Fan; Shengcai Liu; Qing Li 001; Ke Tang 001 (ICDE, 2025)

Leveraging ChatGPT to Empower Training-free Dataset Condensation for Content-based Recommendation. - Jiahao Wu 004; Qijiong Liu; Hengchang Hu; Wenqi Fan; Shengcai Liu; Qing Li 001; Xiao-Ming Wu 003; Ke Tang 001 (WWW (Companion Volume), 2025)

Domain-Agnostic Co-Evolution of Generalizable Parallel Algorithm Portfolios. - Zhiyuan Wang; Shengcai Liu; Peng Yang 008; Ke Tang 001 (CoRR, 2025)

Cascaded Large-Scale TSP Solving with Unified Neural Guidance: Bridging Local and Population-based Search. - Shengcai Liu; Haoze Lv; Zhiyuan Wang; Ke Tang 001 (CoRR, 2025)

Condensing Pre-Augmented Recommendation Data via Lightweight Policy Gradient Estimation. - Jiahao Wu 004; Wenqi Fan; Jingfan Chen; Shengcai Liu; Qijiong Liu; Rui He; Qing Li 001; Ke Tang 001 (IEEE Trans. Knowl. Data Eng., 2025)

Memetic Search for Green Vehicle Routing Problem with Private Capacitated Refueling Stations. - Rui Xu; Xing Fan; Shengcai Liu; Wenjie Chen; Ke Tang 001 (CoRR, 2025)

SemDiff: Generating Natural Unrestricted Adversarial Examples via Semantic Attributes Optimization in Diffusion Models. - Zeyu Dai 001; Shengcai Liu; Rui He; Jiahao Wu 004; Ning Lu 006; Wenqi Fan; Qing Li 001; Ke Tang 001 (CoRR, 2025)

Is PRM Necessary? Problem-Solving RL Implicitly Induces PRM Capability in LLMs. - Zhangying Feng; Qianglong Chen; Ning Lu 006; Yongqian Li; Siqi Cheng; Shuangmu Peng; Duyu Tang; Shengcai Liu; Zhirui Zhang (CoRR, 2025)

Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets. - Ning Lu 006; Shengcai Liu; Jiahao Wu 004; Weiyu Chen; Zhirui Zhang; Yew-Soon Ong; Qi Wang; Ke Tang 001 (CoRR, 2025)

LLM-Driven Instance-Specific Heuristic Generation and Selection. - Shaofeng Zhang; Shengcai Liu; Ning Lu 006; Jiahao Wu 004; Ji Liu; Yew-Soon Ong; Ke Tang 001 (CoRR, 2025)

Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Models. - Ren-Jian Wang; Ke Xue 001; Zeyu Qin; Ziniu Li; Sheng Tang; Hao-Tian Li; Shengcai Liu; Chao Qian 001 (CoRR, 2025)

Scalable Structure Learning of Bayesian Networks by Learning Algorithm Ensembles. - Shengcai Liu; Hui Ouyang; Zhiyuan Wang; Cheng Chen; Qijun Cai; Yew-Soon Ong; Ke Tang 001 (CoRR, 2025)

Knowledge-Guided Memetic Algorithm for Capacitated Arc Routing Problems with Time-Dependent Service Costs. - Qingya Li; Shengcai Liu; Wenjie Chen; Juan Zou; Ke Tang 001; Xin Yao 001 (CoRR, 2025)