| 2025 | AAAI | RLPF: Reinforcement Learning from Prediction Feedback for User Summarization with LLMs. | Jiaxing Wu, Lin Ning, Luyang Liu, Harrison Lee, Neo Wu, Chao Wang, Sushant Prakash, Shawn O'Banion, Bradley Green, Jun Xie |
| 2025 | NAACL | MoDE: Effective Multi-task Parameter Efficient Fine-Tuning with a Mixture of Dyadic Experts. | Lin Ning, Harsh Lara, Meiqi Guo, Abhinav Rastogi |
| 2025 | WWW | User-LLM: Efficient LLM Contextualization with User Embeddings. | Lin Ning, Luyang Liu, Jiaxing Wu, Neo Wu, Devora Berlowitz, Sushant Prakash, Bradley Green, Shawn O'Banion, Jun Xie |
| 2022 | ICLR | What Do We Mean by Generalization in Federated Learning? | Honglin Yuan, Warren Richard Morningstar, Lin Ning, Karan Singhal |
| 2022 | RecSys | EANA: Reducing Privacy Risk on Large-scale Recommendation Models. | Lin Ning, Steve Chien, Shuang Song, Mei Chen, Yunqi Xue, Devora Berlowitz |
| 2021 | ICDM | Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One Stone. | Hui Guan, Umana Chaudhary, Yuanchao Xu, Lin Ning, Lijun Zhang, Xipeng Shen |
| 2021 | ICLR | Simple Augmentation Goes a Long Way: ADRL for DNN Quantization. | Lin Ning, Guoyang Chen, Weifeng Zhang, Xipeng Shen |
| 2019 | ICDE | Adaptive Deep Reuse: Accelerating CNN Training on the Fly. | Lin Ning, Hui Guan, Xipeng Shen |
| 2019 | ICS | Deep reuse: streamline CNN inference on the fly via coarse-grained computation reuse. | Lin Ning, Xipeng Shen |
| 2017 | ICDM | LCD: A Fast Contrastive Divergence Based Algorithm for Restricted Boltzmann Machine. | Lin Ning, Randall Pittman, Xipeng Shen |
| 2017 | PLDI | Generalizations of the theory and deployment of triangular inequality for compiler-based strength reduction. | Yufei Ding, Lin Ning, Hui Guan, Xipeng Shen |
| 2006 | DASC | PIFF: An Intelligent File Filtering Mechanism for Peer-to-Peer Network. | Junda Liu, Lin Ning, Yibo Xue, Dongsheng Wang |