Binhang Yuan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
23
Venues
12
Active years
2016–2026
Best venue rank
A*
Where they publish
Papers
23 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ICDE | HEXGEN-FLOW: Optimizing LLM Inference Request Scheduling for Agentic Text-to-SQL. | You Peng, Youhe Jiang, Wenqi Jiang, Chen Wang, Binhang Yuan |
| 2025 | ACL | Efficient Pretraining Data Selection for Language Models via Multi-Actor Collaboration. | Tianyi Bai, Ling Yang, Zhen Hao Wong, Fupeng Sun, Xinlin Zhuang, Jiahui Peng, Chi Zhang, Lijun Wu, Jiantao Qiu, Wentao Zhang, Binhang Yuan, Conghui He |
| 2025 | ICDE | MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage. | Yongjun He, Roger Waleffe, Zhichao Han, Johnu George, Binhang Yuan, Zitao Zhang, Yinan Shan, Yang Zhao, Debojyoti Dutta, Theodoros Rekatsinas, Ce Zhang |
| 2025 | ICDE | Ratel: Optimizing Holistic Data Movement to Fine-tune 100B Model on a Consumer GPU. | Changyue Liao, Mo Sun, Zihan Yang, Jun Xie, Kaiqi Chen, Binhang Yuan, Fei Wu, Zeke Wang |
| 2025 | ICLR | HexGen-2: Disaggregated Generative Inference of LLMs in Heterogeneous Environment. | Youhe Jiang, Ran Yan, Binhang Yuan |
| 2025 | ICLR | 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 |
| 2025 | ICML | Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs. | Youhe Jiang, Fangcheng Fu, Xiaozhe Yao, Guoliang He, Xupeng Miao, Ana Klimovic, Bin Cui, Binhang Yuan, Eiko Yoneki |
| 2025 | SP | Prompt Inversion Attack Against Collaborative Inference of Large Language Models. | Wenjie Qu, Yuguang Zhou, Yongji Wu, Tingsong Xiao, Binhang Yuan, Yiming Li, Jiaheng Zhang |
| 2025 | USENIX | Toppings: CPU-Assisted, Rank-Aware Adapter Serving for LLM Inference. | Suyi Li, Hanfeng Lu, Tianyuan Wu, Minchen Yu, Qizhen Weng, Xusheng Chen, Yizhou Shan, Binhang Yuan, Wei Wang |
| 2024 | EDBT | 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 |
| 2024 | ICML | HexGen: Generative Inference of Large Language Model over Heterogeneous Environment. | Youhe Jiang, Ran Yan, Xiaozhe Yao, Yang Zhou, Beidi Chen, Binhang Yuan |
| 2024 | ICML | Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training. | Lin Lu, Chenxi Dai, Wangcheng Tao, Binhang Yuan, Yanan Sun, Pan Zhou |
| 2023 | ICML | FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU. | Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher R, Ion Stoica, Ce Zhang |
| 2023 | ICML | Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. | Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher R, Beidi Chen |
| 2023 | ICML | Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning. | Yuxin Tang, Zhimin Ding, Dimitrije Jankov, Binhang Yuan, Daniel Bourgeois, Chris Jermaine |
| 2023 | ICML | CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks. | Jue Wang, Yucheng Lu, Binhang Yuan, Beidi Chen, Percy Liang, Christopher De Sa, Christopher R, Ce Zhang |
| 2022 | HOTNETS | Efficient flow scheduling in distributed deep learning training with echelon formation. | Rui Pan, Yiming Lei, Jialong Li, Zhiqiang Xie, Binhang Yuan, Yiting Xia |
| 2022 | KDD | 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, Honghuan Wu, Lei Sun, Haodong Lyu, Chengjun Liu, Xing Dong, Yiqiao Liao, Mingnan Luo, Congfei Zhang, Jingru Xie, Haonan Li, Lei Chen, Renjie Huang, Jianying Lin, Chengchun Shu, Xuezhong Qiu, Zhishan Liu, Dongying Kong, Lei Yuan, Hai Yu, Sen Yang, Ce Zhang, Ji Liu |
| 2022 | SIGMOD | In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle. | Lijie Xu, Shuang Qiu, Binhang Yuan, Jiawei Jiang, Cdric Renggli, Shaoduo Gan, Kaan Kara, Guoliang Li, Ji Liu, Wentao Wu, Jieping Ye, Ce Zhang |
| 2021 | SIGMOD | Automatic Optimization of Matrix Implementations for Distributed Machine Learning and Linear Algebra. | Shangyu Luo, Dimitrije Jankov, Binhang Yuan, Chris Jermaine |
| 2019 | MICCAI | Diagnosing Cardiac Abnormalities from 12-Lead Electrocardiograms Using Enhanced Deep Convolutional Neural Networks. | Binhang Yuan, Wenhui Xing |
| 2018 | SIGMOD | PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development. | Jia Zou, R. Matthew Barnett, Tania Lorido-Botran, Shangyu Luo, Carlos Monroy, Sourav Sikdar, Kia Teymourian, Binhang Yuan, Chris Jermaine |
| 2016 | ICCS | Generating a 3D Normative Infant Cranial Model. | Binhang Yuan, Ronald N. Goldman, Eric Wang, Olushola Olorunnipa, David Khechoyan |