Effective Video Retargeting With Jittery Assessment. - Bo Yan; Binhang Yuan; Bo Yang (IEEE Trans. Multim., 2014)

Generating a 3D Normative Infant Cranial Model. - Binhang Yuan; Ronald N. Goldman; Eric Wang; Olushola Olorunnipa; David Khechoyan (ICCS, 2016)

Abridging source code. - Binhang Yuan; Vijayaraghavan Murali; Christopher M. Jermaine (Proc. ACM Program. Lang., 2017)

PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development. - Jia Zou 001; R. Matthew Barnett; Tania Lorido-Botran; Shangyu Luo; Carlos Monroy; Sourav Sikdar; Kia Teymourian; Binhang Yuan; Chris Jermaine (SIGMOD Conference, 2018)

Diagnosing Cardiac Abnormalities from 12-Lead Electrocardiograms Using Enhanced Deep Convolutional Neural Networks. - Binhang Yuan; Wenhui Xing (MLMECH/CVII-STENT@MICCAI, 2019)

WaveletFCNN: A Deep Time Series Classification Model for Wind Turbine Blade Icing Detection. - Binhang Yuan; Chen Wang 018; Fei Jiang; Mingsheng Long; Philip S. Yu; Yuan Liu (CoRR, 2019)

Distributed Learning of Deep Neural Networks using Independent Subnet Training. - Binhang Yuan; Anastasios Kyrillidis; Christopher M. Jermaine (CoRR, 2019)

Declarative Recursive Computation on an RDBMS. - Dimitrije Jankov; Shangyu Luo; Binhang Yuan; Zhuhua Cai; Jia Zou 001; Chris Jermaine; Zekai J. Gao (Proc. VLDB Endow., 2019)

A Federated Learning Framework for Healthcare IoT devices. - Binhang Yuan; Song Ge; Wenhui Xing (CoRR, 2020)

Lachesis: Automated Generation of Persistent Partitionings for Big Data Applications. - Jia Zou 001; Pratik Barhate; Amitabh Das; Arun Iyengar; Binhang Yuan; Dimitrije Jankov; Chris Jermaine (CoRR, 2020)

Tensor Relational Algebra for Machine Learning System Design. - Binhang Yuan; Dimitrije Jankov; Jia Zou 001; Yuxin Tang; Daniel Bourgeois; Chris Jermaine (CoRR, 2020)

Declarative Recursive Computation on an RDBMS: or, Why You Should Use a Database For Distributed Machine Learning. - Dimitrije Jankov; Shangyu Luo; Binhang Yuan; Zhuhua Cai; Jia Zou 001; Chris Jermaine; Zekai J. Gao (SIGMOD Rec., 2020)

Automatic Optimization of Matrix Implementations for Distributed Machine Learning and Linear Algebra. - Shangyu Luo; Dimitrije Jankov; Binhang Yuan; Chris Jermaine (SIGMOD Conference, 2021)

BAGUA: Scaling up Distributed Learning with System Relaxations. - Shaoduo Gan; Xiangru Lian; Rui Wang; Jianbin Chang; Chengjun Liu; Hongmei Shi; Shengzhuo Zhang; Xianghong Li; Tengxu Sun; Jiawei Jiang 001; Binhang Yuan; Sen Yang 004; et al. (Proc. VLDB Endow., 2021)

Distributed Numerical and Machine Learning Computations via Two-Phase Execution of Aggregated Join Trees. - Dimitrije Jankov; Binhang Yuan; Shangyu Luo; Chris Jermaine (Proc. VLDB Endow., 2021)

Tensor Relational Algebra for Distributed Machine Learning System Design. - Binhang Yuan; Dimitrije Jankov; Jia Zou 001; Yuxin Tang; Daniel Bourgeois; Chris Jermaine (Proc. VLDB Endow., 2021)

Lachesis: Automated Partitioning for UDF-Centric Analytics. - Jia Zou 001; Amitabh Das; Pratik Barhate; Arun Iyengar; Binhang Yuan; Dimitrije Jankov; Chris Jermaine (Proc. VLDB Endow., 2021)

A Feature Fusion Framework and Its Application to Automatic Seizure Detection. - Chengbin Huang; Weiting Chen; Mingsong Chen 001; Binhang Yuan (IEEE Signal Process. Lett., 2021)

Efficient flow scheduling in distributed deep learning training with echelon formation. - Rui Pan 003; Yiming Lei; Jialong Li 006; Zhiqiang Xie; Binhang Yuan; Yiting Xia (HotNets, 2022)

Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters. - Xiangru Lian; Binhang Yuan; Xuefeng Zhu; Yulong Wang; Yongjun He 004; Honghuan Wu; Lei Sun; Haodong Lyu; Chengjun Liu; Xing Dong; Yiqiao Liao; Mingnan Luo; et al. (KDD, 2022)

Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees. - Jue Wang; Binhang Yuan; Luka Rimanic; Yongjun He 004; Tri Dao; Beidi Chen; Christopher Ré; Ce Zhang 001 (NeurIPS, 2022)

Decentralized Training of Foundation Models in Heterogeneous Environments. - Binhang Yuan; Yongjun He 004; Jared Davis; Tianyi Zhang; Tri Dao; Beidi Chen; Percy Liang; Christopher Ré; Ce Zhang 001 (NeurIPS, 2022)

In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. - Lijie Xu; Shuang Qiu; Binhang Yuan; Jiawei Jiang 001; Cédric Renggli; Shaoduo Gan; Kaan Kara; Guoliang Li 001; Ji Liu 002; Wentao Wu 001; Jieping Ye; Ce Zhang 001 (SIGMOD Conference, 2022)

Fine-tuning Language Models over Slow Networks using Activation Compression with Guarantees. - Jue Wang; Binhang Yuan; Luka Rimanic; Yongjun He 004; Tri Dao; Beidi Chen; Christopher Ré; Ce Zhang 001 (CoRR, 2022)

Stochastic Gradient Descent without Full Data Shuffle. - Lijie Xu; Shuang Qiu; Binhang Yuan; Jiawei Jiang 001; Cédric Renggli; Shaoduo Gan; Kaan Kara; Guoliang Li 001; Ji Liu 002; Wentao Wu 001; Jieping Ye; Ce Zhang 001 (CoRR, 2022)

A community effort to assess and improve computerized interpretation of 12-lead resting electrocardiogram. - Zijian Ding; Guijin Wang; Huazhong Yang; Ping Zhang; Dapeng Fu; Zhen Yang; Xinkang Wang; Xia Wang; Zhourui Xia; Chiming Zhang; Wenjie Cai; Binhang Yuan; et al. (Medical Biol. Eng. Comput., 2022)

Distributed Learning of Fully Connected Neural Networks using Independent Subnet Training. - Binhang Yuan; Cameron R. Wolfe; Chen Dun; Yuxin Tang; Anastasios Kyrillidis; Chris Jermaine (Proc. VLDB Endow., 2022)

Bayesian Hierarchical Model for Change Point Detection in Multivariate Sequences. - Huaqing Jin; Guosheng Yin; Binhang Yuan; Fei Jiang (Technometrics, 2022)

FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU. - Ying Sheng 007; Lianmin Zheng; Binhang Yuan; Zhuohan Li 001; Max Ryabinin; Beidi Chen; Percy Liang; Christopher Ré; Ion Stoica; Ce Zhang 001 (ICML, 2023)

Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. - Zichang Liu; Jue Wang; Tri Dao; Tianyi Zhou 002; Binhang Yuan; Zhao Song 002; Anshumali Shrivastava; Ce Zhang 001; Yuandong Tian; Christopher Ré; Beidi Chen (ICML, 2023)

Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning. - Yuxin Tang; Zhimin Ding; Dimitrije Jankov; Binhang Yuan; Daniel Bourgeois; Chris Jermaine (ICML, 2023)

CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks. - Jue Wang; Yucheng Lu; Binhang Yuan; Beidi Chen; Percy Liang; Christopher De Sa; Christopher Ré; Ce Zhang 001 (ICML, 2023)

High-throughput Generative Inference of Large Language Models with a Single GPU. - Ying Sheng 007; Lianmin Zheng; Binhang Yuan; Zhuohan Li 001; Max Ryabinin; Daniel Y. Fu; Zhiqiang Xie; Beidi Chen; Clark W. Barrett; Joseph E. Gonzalez; Percy Liang; Christopher Ré; et al. (CoRR, 2023)

Serving Deep Learning Model in Relational Databases. - Alexandre E. Eichenberger; Qi Lin; Saif Masood; Hong Min; Alexander Sim; Jie Wang; Yida Wang; Kesheng Wu; Binhang Yuan; Lixi Zhou; Jia Zou 001 (CoRR, 2023)

HexGen: Generative Inference of Foundation Model over Heterogeneous Decentralized Environment. - Youhe Jiang; Ran Yan; Xiaozhe Yao; Beidi Chen; Binhang Yuan (CoRR, 2023)

Exploring the Robustness of Decentralized Training for Large Language Models. - Lin Lu; Chenxi Dai; Wangcheng Tao; Binhang Yuan; Yanan Sun; Pan Zhou 001 (CoRR, 2023)

Holistic Evaluation of Language Models. - Percy Liang; Rishi Bommasani; Tony Lee; Dimitris Tsipras; Dilara Soylu; Michihiro Yasunaga; Yian Zhang; Deepak Narayanan; Yuhuai Wu; Ananya Kumar; Benjamin Newman; Binhang Yuan; et al. (Trans. Mach. Learn. Res., 2023)

Serving Deep Learning Models from Relational Databases. - Lixi Zhou; Qi Lin; Kanchan Chowdhury; Saif Masood; Alexandre E. Eichenberger; Hong Min; Alexander Sim; Jie Wang; Yida Wang; Kesheng Wu; Binhang Yuan; Jia Zou 001 (EDBT, 2024)

HexGen: Generative Inference of Large Language Model over Heterogeneous Environment. - Youhe Jiang; Ran Yan; Xiaozhe Yao; Yang Zhou; Beidi Chen; Binhang Yuan (ICML, 2024)

Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training. - Lin Lu; Chenxi Dai; Wangcheng Tao; Binhang Yuan; Yanan Sun; Pan Zhou 001 (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)

CaraServe: CPU-Assisted and Rank-Aware LoRA Serving for Generative LLM Inference. - Suyi Li 002; Hanfeng Lu; Tianyuan Wu; Minchen Yu; Qizhen Weng; Xusheng Chen; Yizhou Shan; Binhang Yuan; Wei Wang 030 (CoRR, 2024)

Adding NVMe SSDs to Enable and Accelerate 100B Model Fine-tuning on a Single GPU. - Changyue Liao; Mo Sun 001; Zihan Yang; Kaiqi Chen; Binhang Yuan; Fei Wu 001; Zeke Wang (CoRR, 2024)

DeFT: Flash Tree-attention with IO-Awareness for Efficient Tree-search-based LLM Inference. - Jinwei Yao; Kaiqi Chen; Kexun Zhang; Jiaxuan You; Binhang Yuan; Zeke Wang; Tao Lin (CoRR, 2024)

Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model. - Xinrun Du; Zhouliang Yu; Songyang Gao; Ding Pan; Yuyang Cheng; Ziyang Ma 001; Ruibin Yuan; Xingwei Qu; Jiaheng Liu; Tianyu Zheng; Xinchen Luo; Guorui Zhou; et al. (CoRR, 2024)

A Survey of Multimodal Large Language Model from A Data-centric Perspective. - Tianyi Bai; Hao Liang; Binwang Wan; Ling Yang 006; Bozhou Li; Yifan Wang; Bin Cui 001; Conghui He; Binhang Yuan; Wentao Zhang 001 (CoRR, 2024)

On the Opportunities of (Re)-Exploring Atmospheric Science by Foundation Models: A Case Study. - Lujia Zhang; Hanzhe Cui; Yurong Song; Chenyue Li; Binhang Yuan; Mengqian Lu (CoRR, 2024)

FlashFlex: Accommodating Large Language Model Training over Heterogeneous Environment. - Ran Yan; Youhe Jiang; Wangcheng Tao; Xiaonan Nie; Bin Cui 001; Binhang Yuan (CoRR, 2024)

Locret: Enhancing Eviction in Long-Context LLM Inference with Trained Retaining Heads. - Yuxiang Huang; Binhang Yuan; Xu Han 007; Chaojun Xiao; Zhiyuan Liu 001 (CoRR, 2024)

Multi-Agent Collaborative Data Selection for Efficient LLM Pretraining. - Tianyi Bai; Ling Yang 006; Zhen Hao Wong; Jiahui Peng; Xinlin Zhuang; Chi Zhang; Lijun Wu; Jiantao Qiu; Wentao Zhang 001; Binhang Yuan; Conghui He (CoRR, 2024)

Zero-Indexing Internet Search Augmented Generation for Large Language Models. - Guangxin He; Zonghong Dai; Jiangcheng Zhu; Binqiang Zhao; Chenyue Li; You Peng; Chen Wang; Binhang Yuan (CoRR, 2024)

TQA-Bench: Evaluating LLMs for Multi-Table Question Answering with Scalable Context and Symbolic Extension. - Zipeng Qiu; You Peng; Guangxin He; Binhang Yuan; Chen Wang (CoRR, 2024)

Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems. - Lijie Xu; Shuang Qiu; Binhang Yuan; Jiawei Jiang 001; Cédric Renggli; Shaoduo Gan; Kaan Kara; Guoliang Li 001; Ji Liu 002; Wentao Wu 001; Jieping Ye; Ce Zhang 001 (VLDB J., 2024)

Efficient Pretraining Data Selection for Language Models via Multi-Actor Collaboration. - Tianyi Bai; Ling Yang 006; Zhen Hao Wong; Fupeng Sun; Xinlin Zhuang; Jiahui Peng; Chi Zhang; Lijun Wu; Jiantao Qiu; Wentao Zhang 001; Binhang Yuan; Conghui He (ACL (1), 2025)

MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage. - Yongjun He 004; Roger Waleffe; Zhichao Han 001; Johnu George; Binhang Yuan; Zitao Zhang; Yinan Shan; Yang Zhao; Debojyoti Dutta; Theodoros Rekatsinas; Ce Zhang 001 (ICDE, 2025)

Ratel: Optimizing Holistic Data Movement to Fine-tune 100B Model on a Consumer GPU. - Changyue Liao; Mo Sun 001; Zihan Yang; Jun Xie; Kaiqi Chen; Binhang Yuan; Fei Wu 001; Zeke Wang (ICDE, 2025)

HexGen-2: Disaggregated Generative Inference of LLMs in Heterogeneous Environment. - Youhe Jiang; Ran Yan; Binhang Yuan (ICLR, 2025)

DeFT: Decoding with Flash Tree-attention for Efficient Tree-structured LLM Inference. - Jinwei Yao; Kaiqi Chen; Kexun Zhang; Jiaxuan You; Binhang Yuan; Zeke Wang; Tao Lin (ICLR, 2025)

Prompt Inversion Attack Against Collaborative Inference of Large Language Models. - Wenjie Qu 001; Yuguang Zhou; Yongji Wu; Tingsong Xiao; Binhang Yuan; Yiming Li 004; Jiaheng Zhang (SP, 2025)

Toppings: CPU-Assisted, Rank-Aware Adapter Serving for LLM Inference. - Suyi Li 002; Hanfeng Lu; Tianyuan Wu; Minchen Yu; Qizhen Weng; Xusheng Chen; Yizhou Shan; Binhang Yuan; Wei Wang 030 (USENIX ATC, 2025)

Top Ten Challenges Towards Agentic Neural Graph Databases. - Jiaxin Bai; Zihao Wang 001; Yukun Zhou; Hang Yin 008; Weizhi Fei; Qi Hu; Zheye Deng; Jiayang Cheng; Tianshi Zheng; Hong Ting Tsang; Yisen Gao; Zhongwei Xie; et al. (IEEE Data Eng. Bull., 2025)

Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs. - Youhe Jiang; Fangcheng Fu; Xiaozhe Yao; Guoliang He; Xupeng Miao; Ana Klimovic; Bin Cui 001; Binhang Yuan; Eiko Yoneki (CoRR, 2025)

AtmosSci-Bench: Evaluating the Recent Advance of Large Language Model for Atmospheric Science. - Chenyue Li; Wen Deng; Mengqian Lu; Binhang Yuan (CoRR, 2025)

CE-LoRA: Computation-Efficient LoRA Fine-Tuning for Language Models. - Guanduo Chen; Yutong He; Yipeng Hu; Kun Yuan 001; Binhang Yuan (CoRR, 2025)

HEXGEN-TEXT2SQL: Optimizing LLM Inference Request Scheduling for Agentic Text-to-SQL Workflow. - You Peng; Youhe Jiang; Chen Wang; Binhang Yuan (CoRR, 2025)

AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning. - Wei Fu; Jiaxuan Gao; Xujie Shen; Chen Zhu; Zhiyu Mei; Chuyi He; Shusheng Xu; Guo Wei; Jun Mei; Jiashu Wang; Tongkai Yang; Binhang Yuan; et al. (CoRR, 2025)

TAH-QUANT: Effective Activation Quantization in Pipeline Parallelism over Slow Network. - Guangxin He; Yuan Cao; Yutong He; Tianyi Bai; Kun Yuan 001; Binhang Yuan (CoRR, 2025)

Cascadia: A Cascade Serving System for Large Language Models. - Youhe Jiang; Fangcheng Fu; Wanru Zhao; Stephan Rabanser; Nicholas D. Lane; Binhang Yuan (CoRR, 2025)

Hallucination at a Glance: Controlled Visual Edits and Fine-Grained Multimodal Learning. - Tianyi Bai; Yuxuan Fan; Jiantao Qiu; Fupeng Sun; Jiayi Song; Junlin Han; Zichen Liu; Conghui He; Wentao Zhang 001; Binhang Yuan (CoRR, 2025)

Multi-Step Visual Reasoning with Visual Tokens Scaling and Verification. - Tianyi Bai; Zengjie Hu; Fupeng Sun; Jiantao Qiu; Yizhen Jiang; Guangxin He; Bohan Zeng; Conghui He; Binhang Yuan; Wentao Zhang 001 (CoRR, 2025)

Re:Form - Reducing Human Priors in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny. - Chuanhao Yan; Fengdi Che; Xuhan Huang; Xu Xu; Xin Li; Yizhi Li; Xingwei Qu; Jingzhe Shi; Zhuangzhuang He; Chenghua Lin; Yaodong Yang 001; Binhang Yuan; et al. (CoRR, 2025)