Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy. - Pingzhi Li; Zhenyu Zhang 015; Prateek Yadav; Yi-Lin Sung; Yu Cheng 001; Mohit Bansal; Tianlong Chen 001 (ICLR, 2024)

Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark. - Yihua Zhang; Pingzhi Li; Junyuan Hong; Jiaxiang Li; Yimeng Zhang; Wenqing Zheng; Pin-Yu Chen; Jason D. Lee; Wotao Yin; Mingyi Hong 001; Zhangyang Wang; Sijia Liu 001; et al. (ICML, 2024)

Model-GLUE: Democratized LLM Scaling for A Large Model Zoo in the Wild. - Xinyu Zhao; Guoheng Sun; Ruisi Cai; Yukun Zhou; Pingzhi Li; Peihao Wang; Bowen Tan; Yexiao He; Li Chen; Yi Liang; Beidi Chen; Binhang Yuan; et al. (NeurIPS, 2024)

Enhancing Quantum Security over Federated Learning via Post-Quantum Cryptography. - Pingzhi Li; Tianlong Chen 001; Junyu Liu (TPS-ISA, 2024)

Privacy-preserving Fine-tuning of Large Language Models through Flatness. - Tiejin Chen; Longchao Da; Huixue Zhou; Pingzhi Li; Kaixiong Zhou; Tianlong Chen 001; Hua Wei 001 (CoRR, 2024)

Hybrid Quantum-Classical Scheduling for Accelerating Neural Network Training with Newton's Gradient Descent. - Pingzhi Li; Junyu Liu; Hanrui Wang 002; Tianlong Chen 001 (CoRR, 2024)

Examining Post-Training Quantization for Mixture-of-Experts: A Benchmark. - Pingzhi Li; Xiaolong Jin; Yu Cheng 001; Tianlong Chen 001 (CoRR, 2024)

Glider: Global and Local Instruction-Driven Expert Router. - Pingzhi Li; Prateek Yadav; Jaehong Yoon; Jie Peng 002; Yi-Lin Sung; Mohit Bansal; Tianlong Chen 001 (CoRR, 2024)

PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches. - Rana Muhammad Shahroz Khan; Pingzhi Li; Sukwon Yun; Zhenyu Wang; Shahriar Nirjon; Chau-Wai Wong; Tianlong Chen 001 (CoRR, 2024)

HEXA-MoE: Efficient and Heterogeneous-aware MoE Acceleration with ZERO Computation Redundancy. - Shuqing Luo; Jie Peng 002; Pingzhi Li; Tianlong Chen 001 (CoRR, 2024)

Vision Language Model Helps Private Information De-Identification in Vision Data. - Tiejin Chen; Pingzhi Li; Kaixiong Zhou; Tianlong Chen 001; Hua Wei 001 (ACL (Findings), 2025)

Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges. - Tiejin Chen; Pingzhi Li; Kaixiong Zhou; Tianlong Chen 001; Hua Wei 001 (ACL (Findings), 2025)

PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches. - Rana Muhammad Shahroz; Pingzhi Li; Sukwon Yun; Zhenyu Wang; Shahriar Nirjon; Chau-Wai Wong; Tianlong Chen 001 (ICLR, 2025)

Advancing MoE Efficiency: A Collaboration-Constrained Routing (C2R) Strategy for Better Expert Parallelism Design. - Mohan Zhang; Pingzhi Li; Jie Peng 002; Mufan Qiu; Tianlong Chen 001 (NAACL (Long Papers), 2025)

Protecting Privacy against Membership Inference Attack with LLM Fine-tuning through Flatness. - Tiejin Chen; Longchao Da; Huixue Zhou; Pingzhi Li; Kaixiong Zhou; Tianlong Chen 001; Hua Wei 001 (SDM, 2025)

GroverGPT: A Large Language Model with 8 Billion Parameters for Quantum Searching. - Haoran Wang 005; Pingzhi Li; Min Chen; Jinglei Cheng; Junyu Liu; Tianlong Chen 001 (CoRR, 2025)

Make Optimization Once and for All with Fine-grained Guidance. - Mingjia Shi; Ruihan Lin; Xuxi Chen; Yuhao Zhou; Zezhen Ding; Pingzhi Li; Tong Wang; Kai Wang 036; Zhangyang Wang; Jiheng Zhang; Tianlong Chen 001 (CoRR, 2025)

ORAL: Prompting Your Large-Scale LoRAs via Conditional Recurrent Diffusion. - Rana Muhammad Shahroz Khan; Dongwen Tang; Pingzhi Li; Kai Wang 036; Tianlong Chen 001 (CoRR, 2025)

Finding Fantastic Experts in MoEs: A Unified Study for Expert Dropping Strategies and Observations. - Ajay Jaiswal; Jianyu Wang; Yixiao Li; Pingzhi Li; Tianlong Chen 001; Zhangyang Wang; Chong Wang; Ruoming Pang; Xianzhi Du (CoRR, 2025)

GroverGPT-2: Simulating Grover's Algorithm via Chain-of-Thought Reasoning and Quantum-Native Tokenization. - Min Chen; Jinglei Cheng; Pingzhi Li; Haoran Wang 005; Tianlong Chen 001; Junyu Liu (CoRR, 2025)

Occult: Optimizing Collaborative Communication across Experts for Accelerated Parallel MoE Training and Inference. - Shuqing Luo; Pingzhi Li; Jie Peng 002; Hanrui Wang 002; Yang Zhao; Yu Cao; Yu Cheng 001; Tianlong Chen 001 (CoRR, 2025)

DOGe: Defensive Output Generation for LLM Protection Against Knowledge Distillation. - Pingzhi Li; Zhen Tan 001; Huaizhi Qu; Huan Liu 001; Tianlong Chen 001 (CoRR, 2025)