Gravity Effects on Information Filtering and Network Evolving. - Jinhu Liu; Zi-Ke Zhang; Chengcheng Yang; Lingjiao Chen; Chuang Liu 001; Xueqi Wang (CoRR, 2013)

A Novel Public Key Encryption Scheme for Large Image. - Lingjiao Chen; Xinji Chen; Zhigang Peng (TrustCom, 2014)

A novel similarity index for better personalized recommendation. - Lingjiao Chen; Zi-Ke Zhang; Jinhu Liu; Jian Gao; Tao Zhou 001 (CoRR, 2015)

Model-based Pricing: Do Not Pay for More than What You Learn! - Lingjiao Chen; Paraschos Koutris; Arun Kumar 001 (DEEM@SIGMOD, 2017)

When Lempel-Ziv-Welch Meets Machine Learning: A Case Study of Accelerating Machine Learning using Coding. - Fengan Li; Lingjiao Chen; Arun Kumar 001; Jeffrey F. Naughton; Jignesh M. Patel; Xi Wu 001 (CoRR, 2017)

Manifold Assumption and Defenses Against Adversarial Perturbations. - Xi Wu 001; Uyeong Jang; Lingjiao Chen; Somesh Jha (CoRR, 2017)

Towards Linear Algebra over Normalized Data. - Lingjiao Chen; Arun Kumar 001; Jeffrey F. Naughton; Jignesh M. Patel (Proc. VLDB Endow., 2017)

Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training. - Xi Wu 001; Uyeong Jang; Jiefeng Chen 001; Lingjiao Chen; Somesh Jha (ICML, 2018)

DRACO: Byzantine-resilient Distributed Training via Redundant Gradients. - Lingjiao Chen; Hongyi Wang 001; Zachary Charles; Dimitris S. Papailiopoulos (ICML, 2018)

The Effect of Network Width on the Performance of Large-batch Training. - Lingjiao Chen; Hongyi Wang 001; Jinman Zhao; Dimitris S. Papailiopoulos; Paraschos Koutris (NeurIPS, 2018)

A trust-based recommendation method using network diffusion processes. - Lingjiao Chen; Jian Gao (CoRR, 2018)

DRACO: Robust Distributed Training via Redundant Gradients. - Lingjiao Chen; Hongyi Wang 001; Zachary Charles; Dimitris S. Papailiopoulos (CoRR, 2018)

Model-based Pricing for Machine Learning in a Data Marketplace. - Lingjiao Chen; Paraschos Koutris; Arun Kumar 001 (CoRR, 2018)

Towards Model-based Pricing for Machine Learning in a Data Marketplace. - Lingjiao Chen; Paraschos Koutris; Arun Kumar 001 (SIGMOD Conference, 2019)

Demonstration of Nimbus: Model-based Pricing for Machine Learning in a Data Marketplace. - Lingjiao Chen; Hongyi Wang 001; Leshang Chen; Paraschos Koutris; Arun Kumar 001 (SIGMOD Conference, 2019)

Enabling and Optimizing Non-linear Feature Interactions in Factorized Linear Algebra. - Side Li; Lingjiao Chen; Arun Kumar 001 (SIGMOD Conference, 2019)

Tuple-oriented Compression for Large-scale Mini-batch Stochastic Gradient Descent. - Fengan Li; Lingjiao Chen; Yijing Zeng; Arun Kumar 001; Xi Wu 001; Jeffrey F. Naughton; Jignesh M. Patel (SIGMOD Conference, 2019)

FrugalML: How to use ML Prediction APIs more accurately and cheaply. - Lingjiao Chen; Matei Zaharia; James Y. Zou (NeurIPS, 2020)

FrugalMCT: Efficient Online ML API Selection for Multi-Label Classification Tasks. - Lingjiao Chen; Matei Zaharia; James Zou 001 (CoRR, 2021)

Did the Model Change? Efficiently Assessing Machine Learning API Shifts. - Lingjiao Chen; Tracy Cai; Matei Zaharia; James Zou 001 (CoRR, 2021)

Solon: Communication-efficient Byzantine-resilient Distributed Training via Redundant Gradients. - Lingjiao Chen; Leshang Chen; Hongyi Wang 001; Susan B. Davidson; Edgar Dobriban (CoRR, 2021)

SEAL: Interactive Tool for Systematic Error Analysis and Labeling. - Nazneen Rajani; Weixin Liang; Lingjiao Chen; Margaret Mitchell; James Zou 001 (EMNLP (Demos), 2022)

How Did the Model Change? Efficiently Assessing Machine Learning API Shifts. - Lingjiao Chen; Matei Zaharia; James Zou 001 (ICLR, 2022)

Efficient Online ML API Selection for Multi-Label Classification Tasks. - Lingjiao Chen; Matei Zaharia; James Zou 001 (ICML, 2022)

HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions. - Lingjiao Chen; Zhihua Jin; Sabri Eyuboglu; Christopher Ré; Matei Zaharia; James Y. Zou (NeurIPS, 2022)

Estimating and Explaining Model Performance When Both Covariates and Labels Shift. - Lingjiao Chen; Matei Zaharia; James Y. Zou (NeurIPS, 2022)

HAPI Explorer: Comprehension, Discovery, and Explanation on History of ML APIs. - Lingjiao Chen; Zhihua Jin; Sabri Eyuboglu; Huamin Qu; Christopher Ré; Matei Zaharia; James Zou 001 (AAAI, 2023)

DataPerf: Benchmarks for Data-Centric AI Development. - Mark Mazumder; Colby R. Banbury; Xiaozhe Yao; Bojan Karlas; William Gaviria Rojas; Sudnya Frederick Diamos; Greg Diamos; Lynn He; Alicia Parrish; Hannah Rose Kirk; Jessica Quaye; Charvi Rastogi; et al. (NeurIPS, 2023)

How is ChatGPT's behavior changing over time? - Lingjiao Chen; Matei Zaharia; James Zou 001 (CoRR, 2023)

Data Acquisition: A New Frontier in Data-centric AI. - Lingjiao Chen; Bilge Acun; Newsha Ardalani; Yifan Sun 010; Feiyang Kang; Hanrui Lyu; Yongchan Kwon; Ruoxi Jia 001; Carole-Jean Wu; Matei Zaharia; James Zou 001 (CoRR, 2023)

Model ChangeLists: Characterizing Updates to ML Models. - Sabri Eyuboglu; Karan Goel; Arjun Desai; Lingjiao Chen; Mathew Monfort; Christopher Ré; James Zou 001 (FAccT, 2024)

Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews. - Weixin Liang; Zachary Izzo; Yaohui Zhang; Haley Lepp; Hancheng Cao; Xuandong Zhao; Lingjiao Chen; Haotian Ye; Sheng Liu; Zhi Huang; Daniel A. McFarland; James Y. Zou (ICML, 2024)

Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems. - Lingjiao Chen; Jared Quincy Davis; Boris Hanin; Peter Bailis; Ion Stoica; Matei A. Zaharia; James Y. Zou (NeurIPS, 2024)

Are More LLM Calls All You Need? Towards Scaling Laws of Compound Inference Systems. - Lingjiao Chen; Jared Quincy Davis; Boris Hanin; Peter Bailis; Ion Stoica; Matei Zaharia; James Zou 001 (CoRR, 2024)

Networks of Networks: Complexity Class Principles Applied to Compound AI Systems Design. - Jared Quincy Davis; Boris Hanin; Lingjiao Chen; Peter Bailis; Ion Stoica; Matei Zaharia (CoRR, 2024)

Specifications: The missing link to making the development of LLM systems an engineering discipline. - Ion Stoica; Matei Zaharia; Joseph Gonzalez 001; Ken Goldberg; Koushik Sen; Hao Zhang 025; Anastasios Angelopoulos; Shishir G. Patil; Lingjiao Chen; Wei-Lin Chiang; Jared Quincy Davis (CoRR, 2024)

FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance. - Lingjiao Chen; Matei Zaharia; James Zou 001 (Trans. Mach. Learn. Res., 2024)

BARE: Combining Base and Instruction-Tuned Language Models for Better Synthetic Data Generation. - Alan Zhu 001; Parth Asawa; Jared Quincy Davis; Lingjiao Chen; Boris Hanin; Ion Stoica; Joseph E. Gonzalez; Matei Zaharia (CoRR, 2025)

Optimizing Model Selection for Compound AI Systems. - Lingjiao Chen; Jared Quincy Davis; Boris Hanin; Peter Bailis; Matei Zaharia; James Zou 001; Ion Stoica (CoRR, 2025)

Inference-Time Scaling for Complex Tasks: Where We Stand and What Lies Ahead. - Vidhisha Balachandran; Jingya Chen; Lingjiao Chen; Shivam Garg; Neel Joshi; Yash Lara; John Langford 001; Besmira Nushi; Vibhav Vineet; Yue Wu; Safoora Yousefi (CoRR, 2025)

Phi-4-reasoning Technical Report. - Marah I Abdin; Sahaj Agarwal; Ahmed Awadallah 001; Vidhisha Balachandran; Harkirat S. Behl; Lingjiao Chen; Gustavo de Rosa; Suriya Gunasekar; Mojan Javaheripi; Neel Joshi; Piero Kauffmann; Yash Lara; et al. (CoRR, 2025)

MMTU: A Massive Multi-Task Table Understanding and Reasoning Benchmark. - Junjie Xing; Yeye He; Mengyu Zhou; Haoyu Dong 001; Shi Han; Lingjiao Chen; Dongmei Zhang 001; Surajit Chaudhuri; H. V. Jagadish (CoRR, 2025)