From 6a3cad89744b1cc6f5ce99178dabab4d9c5b59cf Mon Sep 17 00:00:00 2001 From: zhisbug Date: Fri, 15 Mar 2024 03:37:26 -0700 Subject: [PATCH] hao update --- README.md | 11 + content/contact.md | 6 +- content/home.md | 2 - content/people.md | 3 +- content/publications.md | 216 +++++++- gen_publications.py | 45 ++ layouts/shortcodes/publication.html | 16 +- public/contact/index.html | 6 +- public/home/index.html | 3 +- public/index.html | 5 +- public/people/index.html | 2 +- public/publications/index.html | 772 +++++++++++++++++++++++++++- publications.json | 567 ++++++++++++++++++++ 13 files changed, 1619 insertions(+), 35 deletions(-) create mode 100644 gen_publications.py create mode 100644 publications.json diff --git a/README.md b/README.md index 6498a1f..433119e 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,14 @@ # hao-ai-lab.github.io This git repo hosts all content displayed on the website of Hao AI Lab @ UCSD. + + +## How to build + +1. Install Hugo > 0.12 +2. Run the following commands: +```bash +git clone https://github.com/hao-ai-lab/hao-ai-lab.github.io.git +cd hao-ai-lab.github.io +hugo server +``` \ No newline at end of file diff --git a/content/contact.md b/content/contact.md index 866073a..7b90a23 100644 --- a/content/contact.md +++ b/content/contact.md @@ -5,10 +5,12 @@ url: "/contact/" summary: contact --- -### Contact for Prospective Lab Members +### Prospective Lab Members {{< justify >}} -Thank you for your interest in our lab at UC San Diego! If you work on machine learning systems and are interested in joining us, please first [**fill out this form**](https://forms.office.com/pages/responsepage.aspx?id=DQSIkWdsW0yxEjajBLZtrQAAAAAAAAAAAANAAa-SsTJUN0NXSDJSU0ExVVZHR0w3RDlHQVM0NDJaOS4u). After submitting the form, please drop professor Hao Zhang an email (haozhang@ucsd.edu). +Thank you for your interest in our lab at UC San Diego! If you work on machine learning and systems, and are interested in joining us, please [**read the page**](https://cseweb.ucsd.edu/~haozhang/prospective_student) on how to get involved. +In general, please first [**fill out this form**](https://forms.office.com/pages/responsepage.aspx?id=DQSIkWdsW0yxEjajBLZtrQAAAAAAAAAAAANAAa-SsTJUN0NXSDJSU0ExVVZHR0w3RDlHQVM0NDJaOS4u). +After submitting the form, please drop an email to Prof. Hao Zhang (haozhang@ucsd.edu). {{< /justify >}} diff --git a/content/home.md b/content/home.md index 5bed0c3..e5d8cbc 100644 --- a/content/home.md +++ b/content/home.md @@ -10,8 +10,6 @@ cover: caption: "Hao AI Lab @ UCSD" --- -### Mission Statement - {{< justify >}} Welcome to the UCSD Hao Lab website! We are passionate about designing strong, efficient, and secure machine learning models and algorithms, and in building scalable, practical distributed systems that can support real-world machine learning workloads. We also develop open-sourced models and systems to democratize the access of Large Language Models (LLMs). We are affiliated with the UCSD ML System Group. diff --git a/content/people.md b/content/people.md index 5fc6d2b..244f068 100644 --- a/content/people.md +++ b/content/people.md @@ -26,8 +26,7 @@ summary: people {{< /lab_members_grid >}} ### Alumni - -{{< alumni category="PhD Students" >}} +{{< alumni >}} {{< alumni_entry name="Hexu Zhao" description="Undergrad Intern, now PhD Student at NYU." homepage="https://github.com/TarzanZhao">}} {{< alumni_entry name="Runyu Lu" description="Undergrad Intern, now PhD Student at UMich." homepage="https://lry89757.github.io/">}} {{< alumni_entry name="Dacheng Li" description="Master's, now PhD Student at UC Berkeley." homepage="https://dachengli1.github.io/">}} diff --git a/content/publications.md b/content/publications.md index ec1678c..dbb10c8 100644 --- a/content/publications.md +++ b/content/publications.md @@ -7,30 +7,232 @@ summary: publications ### 2024 -{{< publication title="CLLMs: Consistency Large Language Models" venue="Arxiv Preprint" paperLink="https://arxiv.org/pdf/2403.00835.pdf" codeLink="https://github.com/hao-ai-lab/Consistency_LLM" data-topic="Efficient LLM Inference" >}} +{{< publication title="CLLMs: Consistency Large Language Models" venue="Preprint 2024" paperLink="https://arxiv.org/pdf/2403.00835.pdf" codeLink="https://github.com/hao-ai-lab/Consistency_LLM" award="" project="" data-topic="Selected, Large Language Models, Scalable ML, ML Systems" >}} Siqi Kou*, Lanxiang Hu*, Zhezhi He, Zhijie Deng, Hao Zhang {{< /publication >}} -{{< publication title="Break the Sequential Dependency of LLM Inference Using Lookahead Decoding" venue="Arxiv Preprint" paperLink="https://arxiv.org/pdf/2402.02057.pdf" codeLink="https://github.com/hao-ai-lab/LookaheadDecoding" data-topic="Efficient LLM Inference" >}} -Yichao Fu, Peter Bailias, Ion Stoica, Hao Zhang +{{< publication title="DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving" venue="Preprint 2024" paperLink="https://arxiv.org/pdf/2401.09670v1.pdf" codeLink="" award="" project="" data-topic="Selected, Large Language Models, ML Systems" >}} +Yinmin Zhong, Shengyu Liu, Junda Chen, Jianbo Hu, Yibo Zhu, Xuanzhe Liu, Xin Jin, Hao Zhang {{< /publication >}} +{{< publication title="Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference" venue="Preprint 2024" paperLink="https://arxiv.org/pdf/2403.04132.pdf" codeLink="https://github.com/lm-sys/FastChat" award="" project="https://chat.lmsys.org/" data-topic="Selected, Large Language Models" >}} +Wei-Lin Chiang*, Lianmin Zheng*, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Banghua Zhu, Hao Zhang, Michael Jordan, Joseph E. Gonzalez, Ion Stoica +{{< /publication >}} + +{{< publication title="APIServe: Efficient API Support for Large-Language Model Inferencing" venue="Preprint 2024" paperLink="https://arxiv.org/pdf/2402.01869.pdf" codeLink="" award="" project="" data-topic="Selected, Large Language Models, ML Systems" >}} +Reyna Abhyankar*, Zijian He*, Vikranth Srivatsa, Hao Zhang, Yiying Zhang +{{< /publication >}} + +{{< publication title="Break the Sequential Dependency of LLM Inference using Lookahead Decoding" venue="Preprint 2024" paperLink="https://arxiv.org/pdf/2402.02057v1.pdf" codeLink="https://github.com/hao-ai-lab/LookaheadDecoding" award="" project="https://lmsys.org/blog/2023-11-21-lookahead-decoding/" data-topic="Selected, Large Language Models, ML Systems" >}} +Yichao Fu, Peter Bailis, Ion Stoica, Hao Zhang +{{< /publication >}}   ### 2023 -{{< publication title="How Long Can Context Length of Open-Source LLMs Truly Promise?" venue="Instruction Workshop @ NeurIPS 2023" paperLink="https://lmsys.org/blog/2023-06-29-longchat/" codeLink="https://github.com/DachengLi1/LongChat" data-topic="Long-context LLM Inference" >}} +{{< publication title="How Long Can Context Length of Open-Source LLMs truly Promise?" venue="Instruction Tuning and Instruction Following Workshop @ NeurIPS 2023 " paperLink="https://openreview.net/pdf?id=LywifFNXV5" codeLink="" award="" project="https://github.com/DachengLi1/LongChat" data-topic="Selected, Large Language Models" >}} Dacheng Li*, Rulin Shao*, Anze Xie, Ying Sheng, Lianmin Zheng, Joseph Gonzalez, Ion Stoica, Xuezhe Ma, Hao Zhang {{< /publication >}} -{{< publication title="Online Speculative Decoding" venue="Arxiv Preprint" paperLink="https://arxiv.org/pdf/2310.07177.pdf" codeLink="https://github.com/LiuXiaoxuanPKU/OSD" data-topic="Efficient LLM Inference" >}} -Xiaoxuan Liu, Lanxiang Hu, Peter Bailias, Ion Stoica, Zhijie Deng, Alvin Cheung, Hao Zhang +{{< publication title="Online Speculative Decoding" venue="Preprint 2023" paperLink="https://arxiv.org/pdf/2310.07177.pdf" codeLink="" award="" project="" data-topic="Selected, Large Language Models, ML Systems, Scalable ML" >}} +Xiaoxuan Liu, Lanxiang Hu, Peter Bailis, Ion Stoica, Zhijie Deng, Alvin Cheung, Hao Zhang {{< /publication >}} -{{< publication title="Lightseq: Sequence Level Parallelism for Distributed Training of Long Context Transformers" venue="Arxiv Preprint" paperLink="https://arxiv.org/pdf/2310.03294.pdf" codeLink="https://github.com/RulinShao/LightSeq" data-topic="ML Systems" >}} +{{< publication title="Lightseq: Sequence Level Parallelism for Distributed Training of Long Context Transformers" venue="Preprint 2023" paperLink="https://arxiv.org/pdf/2310.03294.pdf" codeLink="https://github.com/RulinShao/LightSeq" award="" project="" data-topic="Large Language Models, ML Systems" >}} Dacheng Li*, Rulin Shao*, Anze Xie, Eric P Xing, Joseph E Gonzalez, Ion Stoica, Xuezhe Ma, Hao Zhang {{< /publication >}} +{{< publication title="Efficient Detection of LLM-generated Texts with a Bayesian Surrogate Model" venue="Preprint 2023" paperLink="https://arxiv.org/pdf/2305.16617.pdf" codeLink="" award="" project="" data-topic="Large Language Models, ML Security" >}} +Zhijie Deng*, Hongcheng Gao*, Yibo Miao, Hao Zhang +{{< /publication >}} + +{{< publication title="LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset" venue="ICLR 2024" paperLink="https://arxiv.org/pdf/2309.11998" codeLink="" award="" project="https://huggingface.co/datasets/lmsys/lmsys-chat-1m" data-topic="Selected, Large Language Models" >}} +Lianmin Zheng*, Wei-Lin Chiang*, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric Xing, Joseph E Gonzalez, Ion Stoica, Hao Zhang +{{< /publication >}} + +{{< publication title="Judging LLM-as-a-judge with MT-Bench and Chatbot Arena" venue="NeurIPS 2023" paperLink="https://arxiv.org/pdf/2306.05685" codeLink="https://github.com/lm-sys/FastChat/tree/main/fastchat/llm_judge" award="" project="https://chat.lmsys.org/?arena" data-topic="Selected, Large Language Models" >}} +Lianmin Zheng*, Wei-Lin Chiang*, Ying Sheng*, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, Hao Zhang, Joseph E Gonzalez, Ion Stoica +{{< /publication >}} + +{{< publication title="Evaluating the Robustness of Text-to-image Diffusion Models against Real-world Attacks" venue="Preprint 2023" paperLink="https://arxiv.org/pdf/2306.13103.pdf" codeLink="" award="" project="" data-topic="ML Security" >}} +Hongcheng Gao, Hao Zhang, Yinpeng Dong, Zhijie Deng +{{< /publication >}} + +{{< publication title="Efficient Memory Management for Large Language Model Serving with PagedAttention" venue="SOSP 2023" paperLink="" codeLink="https://github.com/vllm-project/vllm" award="" project="https://vllm.ai/" data-topic="Selected, Large Language Models, ML Systems" >}} +Woosuk Kwon*, Zhuohan Li*, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Yu, Joey Gonzalez, Hao Zhang, Ion Stoica +{{< /publication >}} + +{{< publication title="Vicuna: An Open-source Chatbot Impressing GPT-4 with 90%* Chatgpt Quality" venue="Blogpost 2023" paperLink="https://lmsys.org/blog/2023-03-30-vicuna/" codeLink="https://huggingface.co/lmsys/vicuna-13b-v1.5" award="" project="https://github.com/lm-sys/FastChat" data-topic="Selected, Large Language Models, Large-scale ML Applications" >}} +Wei-Lin Chiang†, Zhuohan Li†, Zi Lin†, Ying Sheng†, Zhanghao Wu†, Hao Zhang†, Lianmin Zheng†, Siyuan Zhuang†, Yonghao Zhuang†, Joseph E Gonzalez†, Ion Stoica†, Eric P Xing† +{{< /publication >}} + +{{< publication title="AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving" venue="OSDI 2023" paperLink="https://arxiv.org/pdf/2302.11665.pdf" codeLink="https://github.com/alpa-projects/mms" award="" project="https://alpa.ai/opt" data-topic="Selected, ML Systems, Large Language Models" >}} +Zhuohan Li*, Lianmin Zheng*, Yinmin Zhong*, Vincent Liu, Ying Sheng, Xin Jin, Yanping Huang, Zhifeng Chen, Hao Zhang, Joseph E Gonzalez, Ion Stoica +{{< /publication >}} +   +### 2022 + +{{< publication title="On Optimizing the Communication of Model Parallelism" venue="MLSYS 2023" paperLink="https://arxiv.org/pdf/2211.05322.pdf" codeLink="https://github.com/alpa-projects/alpa/blob/main/alpa/pipeline_parallel/cross_mesh_resharding.py" award="" project="" data-topic="Selected, ML Systems, Large Language Models" >}} +Yonghao Zhuang*, Hexu Zhao*, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph E. Gonzalez, Ion Stoica, Hao Zhang +{{< /publication >}} + +{{< publication title="AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness" venue="NeurIPS 2022" paperLink="https://proceedings.neurips.cc/paper_files/paper/2022/file/2b4bfa1cebe78d125fefd7ea6ffcfc6d-Paper-Conference.pdf" codeLink="https://github.com/DachengLi1/AMP" award="" project="" data-topic="ML Systems, Large Language Models, Scalable ML" >}} +Dacheng Li, Hongyi Wang, Eric Xing, Hao Zhang +{{< /publication >}} + +{{< publication title="MPCFormer: Fast, Performant and Private Transformer Inference with MPC" venue="ICLR 2023" paperLink="https://arxiv.org/pdf/2211.01452.pdf" codeLink="https://github.com/DachengLi1/MPCFormer" award="Notable-top-25%" project="" data-topic="Selected, Large Language Models, ML Security" >}} +Dacheng Li*, Rulin Shao*, Hongyi Wang*, Han Guo, Eric P. Xing, Hao Zhang +{{< /publication >}} + +{{< publication title="Neural Eigenfunctions Are Structured Representation Learners" venue="Preprint 2022" paperLink="https://arxiv.org/pdf/2210.12637" codeLink="" award="" project="" data-topic="Scalable ML" >}} +Zhijie Deng, Jiaxin Shi, Hao Zhang, Peng Cui, Cewu Lu, Jun Zhu +{{< /publication >}} + +{{< publication title="Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning" venue="OSDI 2022" paperLink="https://arxiv.org/pdf/2201.12023.pdf" codeLink="" award="" project="https://alpa.ai/" data-topic="Selected, Large Language Models, ML Systems" >}} +Lianmin Zheng*, Zhuohan Li*, Hao Zhang*, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica +{{< /publication >}} + +  + +### 2021 + +{{< publication title="Ada-segment: Automated Multi-loss Adaptation for Panoptic Segmentation" venue="AAAI 2021" paperLink="https://ojs.aaai.org/index.php/AAAI/article/download/16445/16252" codeLink="" award="" project="" data-topic="AutoML, Large-scale ML Applications" >}} +Gengwei Zhang, Yiming Gao, Hang Xu, Hao Zhang, Zhenguo Li, Xiaodan Liang +{{< /publication >}} + +{{< publication title="Terapipe: Token-level Pipeline Parallelism for Training Large-scale Language Models" venue="ICML 2021" paperLink="https://arxiv.org/pdf/2102.07988.pdf" codeLink="https://github.com/zhuohan123/terapipe" award="" project="" data-topic="Selected, Large Language Models, ML Systems, Scalable ML" >}} +Zhuohan Li, Siyuan Zhuang, Shiyuan Guo, Danyang Zhuo, Hao Zhang, Dawn Song, Ion Stoica +{{< /publication >}} + +  + +### 2020 + +{{< publication title="Pollux: Co-adaptive Cluster Scheduling for Goodput-optimized Deep Learning" venue="OSDI 2021" paperLink="https://arxiv.org/pdf/2008.12260.pdf" codeLink="https://github.com/petuum/adaptdl" award="Jay Lepreau Best Paper Award" project="" data-topic="Selected, ML Systems" >}} +Aurick Qiao, Sang Keun Choe, Suhas Jayaram Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R Ganger, Eric P Xing +{{< /publication >}} + +{{< publication title="Machine Learning Parallelism Could Be Adaptive, Composable, and Automated" venue="CMU PhD Dissertation 2020" paperLink="https://kilthub.cmu.edu/ndownloader/files/27533894" codeLink="" award="" project="" data-topic="Selected, ML Systems, Scalable ML, AutoML" >}} +Hao Zhang +{{< /publication >}} + +{{< publication title="Autosync: Learning to Synchronize for Data-parallel Distributed Deep Learning" venue="NeurIPS 2020" paperLink="https://proceedings.neurips.cc/paper/2020/file/0a2298a72858d90d5c4b4fee954b6896-Paper.pdf" codeLink="https://github.com/petuum/autodist" award="" project="" data-topic="Selected, ML Systems, Scalable ML, AutoML" >}} +Hao Zhang*, Yuan Li*, Zhijie Deng, Xiaodan Liang, Lawrence Carin, Eric Xing +{{< /publication >}} + +  + +### 2018 + +{{< publication title="Toward Understanding the Impact of Staleness in Distributed Machine Learning" venue="ICLR 2019" paperLink="https://arxiv.org/pdf/1810.03264.pdf" codeLink="" award="" project="" data-topic="Selected, Scalable ML" >}} +Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric P Xing +{{< /publication >}} + +{{< publication title="Autoloss: Learning Discrete Schedules for Alternate Optimization" venue="ICLR 2019" paperLink="https://arxiv.org/pdf/1810.03264.pdf" codeLink="https://github.com/safpla/AutoLossRelease" award="" project="" data-topic="AutoML" >}} +Haowen Xu*, Hao Zhang*, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric Xing +{{< /publication >}} + +{{< publication title="Symbolic Graph Reasoning Meets Convolutions" venue="NeurIPS 2018" paperLink="https://proceedings.neurips.cc/paper_files/paper/2018/file/cbb6a3b884f4f88b3a8e3d44c636cbd8-Paper.pdf" codeLink="" award="" project="" data-topic="Large-scale ML Applications" >}} +Xiaodan Liang, Zhiting Hu, Hao Zhang, Liang Lin, Eric P Xing +{{< /publication >}} + +{{< publication title="Generative Semantic Manipulation with Mask-contrasting GAN" venue="ECCV 2018" paperLink="https://openaccess.thecvf.com/content_ECCV_2018/papers/Liang_Generative_Semantic_Manipulation_ECCV_2018_paper.pdf" codeLink="" award="" project="" data-topic="Large-scale ML Applications" >}} +Xiaodan Liang, Hao Zhang, Liang Lin, Eric Xing +{{< /publication >}} + +  + +### 2017 + +{{< publication title="Scan: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays" venue="Workshop on Deep Learning in Medical Image Analysis 2019" paperLink="https://arxiv.org/pdf/1703.08770.pdf" codeLink="" award="" project="" data-topic="Healthcare" >}} +Wei Dai, Nanqing Dong, Zeya Wang, Xiaodan Liang, Hao Zhang, Eric P Xing +{{< /publication >}} + +{{< publication title="Cavs: An Efficient Runtime System for Dynamic Neural Networks" venue="ATC 2018" paperLink="https://www.usenix.org/system/files/conference/atc18/atc18-xu-shizhen.pdf" codeLink="https://github.com/zhisbug/Cavs" award="" project="" data-topic="Selected, ML Systems" >}} +Shizhen Xu*, Hao Zhang*, Graham Neubig, Wei Dai, Jin Kyu Kim, Zhijie Deng, Qirong Ho, Guangwen Yang, Eric P Xing +{{< /publication >}} + +{{< publication title="Zm-net: Real-time Zero-shot Image Manipulation Network" venue="Preprint 2017" paperLink="https://arxiv.org/pdf/1703.07255" codeLink="" award="" project="" data-topic="Large-scale ML Applications" >}} +Hao Wang, Xiaodan Liang, Hao Zhang, Dit-Yan Yeung, Eric P Xing +{{< /publication >}} + +{{< publication title="Structured Generative Adversarial Networks" venue="NeurIPS 2017" paperLink="https://proceedings.neurips.cc/paper/2017/file/c3535febaff29fcb7c0d20cbe94391c7-Paper.pdf" codeLink="https://github.com/thudzj/StructuredGAN" award="Nvidia Pioneer Research Award" project="" data-topic="Scalable ML, Large-scale ML Applications" >}} +Zhijie Deng*, Hao Zhang*, Xiaodan Liang, Luona Yang, Shizhen Xu, Jun Zhu, Eric P Xing +{{< /publication >}} + +{{< publication title="Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters" venue="ATC 2017" paperLink="https://www.usenix.org/system/files/conference/atc17/atc17-zhang.pdf" codeLink="https://github.com/sailing-pmls/pmls-caffe" award="" project="https://poseidon-release.readthedocs.io/en/v1.0.1/" data-topic="Selected, ML Systems" >}} +Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Eric P Xing +{{< /publication >}} + +{{< publication title="Recurrent Topic-transition GAN for Visual Paragraph Generation" venue="ICCV 2017" paperLink="https://openaccess.thecvf.com/content_ICCV_2017/papers/Liang_Recurrent_Topic-Transition_GAN_ICCV_2017_paper.pdf" codeLink="" award="" project="" data-topic="Large-scale ML Applications" >}} +Xiaodan Liang, Zhiting Hu, Hao Zhang, Chuang Gan, Eric P Xing +{{< /publication >}} + +  + +### 2016 + +{{< publication title="On the Reducibility of Submodular Functions" venue="AISTATS 2016" paperLink="http://proceedings.mlr.press/v51/mei16.pdf" codeLink="" award="" project="" data-topic="Scalable ML" >}} +Jincheng Mei, Hao Zhang, Bao-Liang Lu +{{< /publication >}} + +{{< publication title="Geeps: Scalable Deep Learning on Distributed GPUs with a GPU-specialized Parameter Server" venue="EUROSYS 2016" paperLink="https://dl.acm.org/doi/pdf/10.1145/2901318.2901323" codeLink="https://github.com/cuihenggang/geeps" award="" project="" data-topic="Selected, ML Systems" >}} +Henggang Cui, Hao Zhang, Gregory R Ganger, Phillip B Gibbons, Eric P Xing +{{< /publication >}} + +{{< publication title="Combining the Best of Convolutional Layers and Recurrent Layers: A Hybrid Network for Semantic Segmentation" venue="Preprint 2016" paperLink="https://arxiv.org/pdf/1603.04871.pdf" codeLink="" award="" project="" data-topic="Large-scale ML Applications" >}} +Zhicheng Yan, Hao Zhang, Yangqing Jia, Thomas Breuel, Yizhou Yu +{{< /publication >}} + +{{< publication title="Learning Concept Taxonomies from Multi-modal Data" venue="ACL 2016" paperLink="https://arxiv.org/pdf/1606.09239.pdf" codeLink="" award="" project="" data-topic="Large-scale ML Applications" >}} +Hao Zhang, Zhiting Hu, Yuntian Deng, Mrinmaya Sachan, Zhicheng Yan, Eric P. Xing +{{< /publication >}} + +  + +### 2015 + +{{< publication title="Automatic Photo Adjustment Using Deep Neural Networks" venue="ACM Transactions on Graphics 2015" paperLink="https://arxiv.org/pdf/1412.7725.pdf" codeLink="https://github.com/stephenyan1231/dl-image-enhance" award="" project="" data-topic="Selected, Large-scale ML Applications" >}} +Zhicheng Yan, Hao Zhang, Baoyuan Wang, Sylvain Paris, Yizhou Yu +{{< /publication >}} + +{{< publication title="Dynamic Topic Modeling for Monitoring Market Competition from Online Text and Image Data" venue="KDD 2015" paperLink="https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=848442f9ec47f3c310c3edaf2efc1477172db227" codeLink="" award="" project="https://people.eecs.berkeley.edu/~hao/projects/BrandCompetition/brandcompetition.html" data-topic="Large-scale ML Applications, Scalable ML" >}} +Hao Zhang, Gunhee Kim, Eric P Xing +{{< /publication >}} + +{{< publication title="A Boosting-Based Spatial-Spectral Model for Stroke Patients' EEG Analysis in Rehabilitation Training" venue="Transactions on Neural Systems and Rehabilitation Engineering 2015" paperLink="https://people.eecs.berkeley.edu/~hao/projects/BSSM-TNSRE/07214285.pdf" codeLink="" award="" project="" data-topic="Healthcare" >}} +Ye Liu, Hao Zhang, Min Chen, Liqing Zhang +{{< /publication >}} + +{{< publication title="HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition" venue="ICCV 2015" paperLink="https://openaccess.thecvf.com/content_iccv_2015/papers/Yan_HD-CNN_Hierarchical_Deep_ICCV_2015_paper.pdf" codeLink="https://paperswithcode.com/paper/hd-cnn-hierarchical-deep-convolutional-neural#code" award="" project="" data-topic="Selected, Large-scale ML Applications, Scalable ML" >}} +Zhicheng Yan, Hao Zhang, Robinson Piramuthu, Vignesh Jagadeesh, Dennis DeCoste, Wei Di, Yizhou Yu +{{< /publication >}} + +  + +### 2014 + +{{< publication title="A Tensor-based Scheme for Stroke Patients’ Motor Imagery EEG Analysis in BCI-FES Rehabilitation Training" venue="Journal of neuroscience methods 2014" paperLink="https://bcmi.sjtu.edu.cn/~zhangliqing/Papers/2014JNM-StrokePatients-Liu.pdf" codeLink="" award="" project="" data-topic="Healthcare" >}} +Ye Liu, Mingfen Li, Hao Zhang, Hang Wang, Junhua Li, Jie Jia, Yi Wu, Liqing Zhang +{{< /publication >}} + +{{< publication title="Common Spatial-spectral Boosting Pattern for Brain-computer Interface" venue="ECAI 2014" paperLink="https://ebooks.iospress.nl/pdf/doi/10.3233/978-1-61499-419-0-537" codeLink="" award="" project="" data-topic="Healthcare" >}} +Ye Liu, Hao Zhang, Qibin Zhao, Liqing Zhang +{{< /publication >}} + +  + +### 2013 + +{{< publication title="Gaussian Mixture Modeling in Stroke Patients' Rehabilitation EEG Data Analysis" venue="EMBC 2013" paperLink="http://139.91.210.27/CBML/PROCEEDINGS/2013_EMBC/PDFs/Papers/05861329.pdf" codeLink="" award="" project="" data-topic="Healthcare" >}} +Hao Zhang, Ye Liu, Jianyi Liang, Jianting Cao, Liqing Zhang +{{< /publication >}} + +{{< publication title="Single-trial Discrimination of EEG Signals for Stroke Patients: a General Multi-way Analysis" venue="EMBC 2013" paperLink="https://people.eecs.berkeley.edu/~hao/projects/TensorJNM/06609973.pdf" codeLink="" award="" project="" data-topic="Healthcare" >}} +Ye Liu, Mingfen Li, Hao Zhang, Junhua Li, Jie Jia, Yi Wu, Jianting Cao, Liqing Zhang +{{< /publication >}} + +  diff --git a/gen_publications.py b/gen_publications.py new file mode 100644 index 0000000..bbd3707 --- /dev/null +++ b/gen_publications.py @@ -0,0 +1,45 @@ +import json +from collections import defaultdict + +# Function to convert JSON to Hugo format +def convert_json_to_hugo(publications): + # Organize publications by year + publications_by_year = defaultdict(list) + for publication in publications: + year = publication["date"].split("/")[1] + publications_by_year[year].append(publication) + + # Sort years in descending order + sorted_years = sorted(publications_by_year.keys(), reverse=True) + + # Format publications for Hugo + hugo_output = "" + for year in sorted_years: + hugo_output += f"### {year}\n\n" + for publication in publications_by_year[year]: + title = publication["title"] + venue = publication.get("venue", "") + paper_link = publication.get("pdf", "") + code_link = publication.get("code", "") + authors = publication["authors"] + # Assuming 'data-topic' needs to be manually adjusted or derived from 'tag' + data_topic = publication["tag"] # This is a placeholder, adjust as needed + award = publication["award"] + project = publication["project"] + + hugo_output += (f"{{{{< publication title=\"{title}\" venue=\"{venue}\" " + f"paperLink=\"{paper_link}\" codeLink=\"{code_link}\" " + f"award=\"{award}\" project=\"{project}\" data-topic=\"{data_topic}\" >}}}}\n") + hugo_output += f"{authors}\n" + hugo_output += "{{< /publication >}}\n\n" + hugo_output += " \n\n" + + return hugo_output + +# Load JSON data from file +with open('publications.json', 'r') as file: + publications_json = json.load(file) + +# Convert and print the Hugo formatted string +hugo_format = convert_json_to_hugo(publications_json) +print(hugo_format) diff --git a/layouts/shortcodes/publication.html b/layouts/shortcodes/publication.html index efd93a8..2ff2f54 100644 --- a/layouts/shortcodes/publication.html +++ b/layouts/shortcodes/publication.html @@ -1,6 +1,18 @@
-

{{ .Get "title" }}
+

+ {{ .Get "title" }}
{{ .Inner }}
- {{ .Get "venue" }} (Paper, Code) + {{ .Get "venue" }} + {{ with .Get "award" }} + ({{ . }}) + {{ end }} + +
+ {{ with .Get "codeLink" }} + [code] + {{ end }} + {{ with .Get "project" }} + [project] + {{ end }}

diff --git a/public/contact/index.html b/public/contact/index.html index 87e2963..deeafcd 100644 --- a/public/contact/index.html +++ b/public/contact/index.html @@ -166,9 +166,11 @@

-

Contact for Prospective Lab Members

+

Prospective Lab Members

- Thank you for your interest in our lab at UC San Diego! If you work on machine learning systems and are interested in joining us, please first fill out this form. After submitting the form, please drop professor Hao Zhang an email (haozhang@ucsd.edu). + Thank you for your interest in our lab at UC San Diego! If you work on machine learning and systems, and are interested in joining us, please read the page on how to get involved. +In general, please first fill out this form. +After submitting the form, please drop an email to Prof. Hao Zhang (haozhang@ucsd.edu).
diff --git a/public/home/index.html b/public/home/index.html index 6149f75..00ede2d 100644 --- a/public/home/index.html +++ b/public/home/index.html @@ -169,8 +169,7 @@

Hao AI Lab @ UCSD

Hao AI Lab @ UCSD

-

Mission Statement

-
+
Welcome to the UCSD Hao Lab website! We are passionate about designing strong, efficient, and secure machine learning models and algorithms, and in building scalable, practical distributed systems that can support real-world machine learning workloads. We also develop open-sourced models and systems to democratize the access of Large Language Models (LLMs). We are affiliated with the UCSD ML System Group.
diff --git a/public/index.html b/public/index.html index 971490a..ae49e7a 100644 --- a/public/index.html +++ b/public/index.html @@ -2,7 +2,7 @@ - + @@ -181,8 +181,7 @@

-

Mission Statement

-
+
Welcome to the UCSD Hao Lab website! We are passionate about designing strong, efficient, and secure machine learning models and algorithms, and in building scalable, practical distributed systems that can support real-world machine learning workloads. We also develop open-sourced models and systems to democratize the access of Large Language Models (LLMs). We are affiliated with the UCSD ML System Group.
diff --git a/public/people/index.html b/public/people/index.html index 0086a01..c81984e 100644 --- a/public/people/index.html +++ b/public/people/index.html @@ -483,7 +483,7 @@

Alumni

    -

    CLLMs: Consistency Large Language Models
    +

    + CLLMs: Consistency Large Language Models
    Siqi Kou*, Lanxiang Hu*, Zhezhi He, Zhijie Deng, Hao Zhang
    - Arxiv Preprint (Paper, Code) + Preprint 2024 + + +
    + + [code] + + +

    +
    + +
    +

    + DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving
    + +Yinmin Zhong, Shengyu Liu, Junda Chen, Jianbo Hu, Yibo Zhu, Xuanzhe Liu, Xin Jin, Hao Zhang +
    + Preprint 2024 + + +
    + +

    -

    Break the Sequential Dependency of LLM Inference Using Lookahead Decoding
    +

    + Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference
    -Yichao Fu, Peter Bailias, Ion Stoica, Hao Zhang +Wei-Lin Chiang*, Lianmin Zheng*, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Banghua Zhu, Hao Zhang, Michael Jordan, Joseph E. Gonzalez, Ion Stoica
    - Arxiv Preprint (Paper, Code) + Preprint 2024 + + +
    + + [code] + + + [project] + +

    +
    + +
    +

    + APIServe: Efficient API Support for Large-Language Model Inferencing
    + +Reyna Abhyankar*, Zijian He*, Vikranth Srivatsa, Hao Zhang, Yiying Zhang +
    + Preprint 2024 + + +
    + + +

    +
    + +
    +

    + Break the Sequential Dependency of LLM Inference using Lookahead Decoding
    + +Yichao Fu, Peter Bailis, Ion Stoica, Hao Zhang +
    + Preprint 2024 + + +
    + + [code] + + + [project] +

     

    2023

    -

    How Long Can Context Length of Open-Source LLMs Truly Promise?
    +

    + How Long Can Context Length of Open-Source LLMs truly Promise?
    Dacheng Li*, Rulin Shao*, Anze Xie, Ying Sheng, Lianmin Zheng, Joseph Gonzalez, Ion Stoica, Xuezhe Ma, Hao Zhang
    - Instruction Workshop @ NeurIPS 2023 (Paper, Code) + Instruction Tuning and Instruction Following Workshop @ NeurIPS 2023 + + +
    + + + [project] +

    -

    Online Speculative Decoding
    +

    + Online Speculative Decoding
    -Xiaoxuan Liu, Lanxiang Hu, Peter Bailias, Ion Stoica, Zhijie Deng, Alvin Cheung, Hao Zhang +Xiaoxuan Liu, Lanxiang Hu, Peter Bailis, Ion Stoica, Zhijie Deng, Alvin Cheung, Hao Zhang
    - Arxiv Preprint (Paper, Code) + Preprint 2023 + + +
    + +

    -

    Lightseq: Sequence Level Parallelism for Distributed Training of Long Context Transformers
    +

    + Lightseq: Sequence Level Parallelism for Distributed Training of Long Context Transformers
    Dacheng Li*, Rulin Shao*, Anze Xie, Eric P Xing, Joseph E Gonzalez, Ion Stoica, Xuezhe Ma, Hao Zhang
    - Arxiv Preprint (Paper, Code) + Preprint 2023 + + +
    + + [code] + + +

    +
    + +
    +

    + Efficient Detection of LLM-generated Texts with a Bayesian Surrogate Model
    + +Zhijie Deng*, Hongcheng Gao*, Yibo Miao, Hao Zhang +
    + Preprint 2023 + + +
    + + +

    +
    + +
    +

    + LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset
    + +Lianmin Zheng*, Wei-Lin Chiang*, Ying Sheng, Tianle Li, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zhuohan Li, Zi Lin, Eric Xing, Joseph E Gonzalez, Ion Stoica, Hao Zhang +
    + ICLR 2024 + + +
    + + + [project] + +

    +
    + +
    +

    + Judging LLM-as-a-judge with MT-Bench and Chatbot Arena
    + +Lianmin Zheng*, Wei-Lin Chiang*, Ying Sheng*, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, Hao Zhang, Joseph E Gonzalez, Ion Stoica +
    + NeurIPS 2023 + + +
    + + [code] + + + [project] + +

    +
    + +
    +

    + Evaluating the Robustness of Text-to-image Diffusion Models against Real-world Attacks
    + +Hongcheng Gao, Hao Zhang, Yinpeng Dong, Zhijie Deng +
    + Preprint 2023 + + +
    + + +

    +
    + +
    +

    + Efficient Memory Management for Large Language Model Serving with PagedAttention
    + +Woosuk Kwon*, Zhuohan Li*, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Yu, Joey Gonzalez, Hao Zhang, Ion Stoica +
    + SOSP 2023 + + +
    + + [code] + + + [project] + +

    +
    + +
    +

    + Vicuna: An Open-source Chatbot Impressing GPT-4 with 90%* Chatgpt Quality
    + +Wei-Lin Chiang†, Zhuohan Li†, Zi Lin†, Ying Sheng†, Zhanghao Wu†, Hao Zhang†, Lianmin Zheng†, Siyuan Zhuang†, Yonghao Zhuang†, Joseph E Gonzalez†, Ion Stoica†, Eric P Xing† +
    + Blogpost 2023 + + +
    + + [code] + + + [project] + +

    +
    + +
    +

    + AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving
    + +Zhuohan Li*, Lianmin Zheng*, Yinmin Zhong*, Vincent Liu, Ying Sheng, Xin Jin, Yanping Huang, Zhifeng Chen, Hao Zhang, Joseph E Gonzalez, Ion Stoica +
    + OSDI 2023 + + +
    + + [code] + + + [project] + +

    +
    + +

     

    +

    2022

    +
    +

    + On Optimizing the Communication of Model Parallelism
    + +Yonghao Zhuang*, Hexu Zhao*, Lianmin Zheng, Zhuohan Li, Eric P. Xing, Qirong Ho, Joseph E. Gonzalez, Ion Stoica, Hao Zhang +
    + MLSYS 2023 + + +
    + + [code] + + +

    +
    + +
    +

    + AMP: Automatically Finding Model Parallel Strategies with Heterogeneity Awareness
    + +Dacheng Li, Hongyi Wang, Eric Xing, Hao Zhang +
    + NeurIPS 2022 + + +
    + + [code] + + +

    +
    + +
    +

    + MPCFormer: Fast, Performant and Private Transformer Inference with MPC
    + +Dacheng Li*, Rulin Shao*, Hongyi Wang*, Han Guo, Eric P. Xing, Hao Zhang +
    + ICLR 2023 + + (Notable-top-25%) + + +
    + + [code] + + +

    +
    + +
    +

    + Neural Eigenfunctions Are Structured Representation Learners
    + +Zhijie Deng, Jiaxin Shi, Hao Zhang, Peng Cui, Cewu Lu, Jun Zhu +
    + Preprint 2022 + + +
    + + +

    +
    + +
    +

    + Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning
    + +Lianmin Zheng*, Zhuohan Li*, Hao Zhang*, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica +
    + OSDI 2022 + + +
    + + + [project] + +

    +
    + +

     

    +

    2021

    +
    +

    + Ada-segment: Automated Multi-loss Adaptation for Panoptic Segmentation
    + +Gengwei Zhang, Yiming Gao, Hang Xu, Hao Zhang, Zhenguo Li, Xiaodan Liang +
    + AAAI 2021 + + +
    + + +

    +
    + +
    +

    + Terapipe: Token-level Pipeline Parallelism for Training Large-scale Language Models
    + +Zhuohan Li, Siyuan Zhuang, Shiyuan Guo, Danyang Zhuo, Hao Zhang, Dawn Song, Ion Stoica +
    + ICML 2021 + + +
    + + [code] + + +

    +
    + +

     

    +

    2020

    +
    +

    + Pollux: Co-adaptive Cluster Scheduling for Goodput-optimized Deep Learning
    + +Aurick Qiao, Sang Keun Choe, Suhas Jayaram Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R Ganger, Eric P Xing +
    + OSDI 2021 + + (Jay Lepreau Best Paper Award) + + +
    + + [code] + + +

    +
    + +
    +

    + Machine Learning Parallelism Could Be Adaptive, Composable, and Automated
    + +Hao Zhang +
    + CMU PhD Dissertation 2020 + + +
    + + +

    +
    + +
    +

    + Autosync: Learning to Synchronize for Data-parallel Distributed Deep Learning
    + +Hao Zhang*, Yuan Li*, Zhijie Deng, Xiaodan Liang, Lawrence Carin, Eric Xing +
    + NeurIPS 2020 + + +
    + + [code] + + +

    +
    + +

     

    +

    2018

    +
    +

    + Toward Understanding the Impact of Staleness in Distributed Machine Learning
    + +Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric P Xing +
    + ICLR 2019 + + +
    + + +

    +
    + +
    +

    + Autoloss: Learning Discrete Schedules for Alternate Optimization
    + +Haowen Xu*, Hao Zhang*, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric Xing +
    + ICLR 2019 + + +
    + + [code] + + +

    +
    + +
    +

    + Symbolic Graph Reasoning Meets Convolutions
    + +Xiaodan Liang, Zhiting Hu, Hao Zhang, Liang Lin, Eric P Xing +
    + NeurIPS 2018 + + +
    + + +

    +
    + +
    +

    + Generative Semantic Manipulation with Mask-contrasting GAN
    + +Xiaodan Liang, Hao Zhang, Liang Lin, Eric Xing +
    + ECCV 2018 + + +
    + + +

    +
    + +

     

    +

    2017

    +
    +

    + Scan: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays
    + +Wei Dai, Nanqing Dong, Zeya Wang, Xiaodan Liang, Hao Zhang, Eric P Xing +
    + Workshop on Deep Learning in Medical Image Analysis 2019 + + +
    + + +

    +
    + +
    +

    + Cavs: An Efficient Runtime System for Dynamic Neural Networks
    + +Shizhen Xu*, Hao Zhang*, Graham Neubig, Wei Dai, Jin Kyu Kim, Zhijie Deng, Qirong Ho, Guangwen Yang, Eric P Xing +
    + ATC 2018 + + +
    + + [code] + + +

    +
    + +
    +

    + Zm-net: Real-time Zero-shot Image Manipulation Network
    + +Hao Wang, Xiaodan Liang, Hao Zhang, Dit-Yan Yeung, Eric P Xing +
    + Preprint 2017 + + +
    + + +

    +
    + +
    +

    + Structured Generative Adversarial Networks
    + +Zhijie Deng*, Hao Zhang*, Xiaodan Liang, Luona Yang, Shizhen Xu, Jun Zhu, Eric P Xing +
    + NeurIPS 2017 + + (Nvidia Pioneer Research Award) + + +
    + + [code] + + +

    +
    + +
    +

    + Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters
    + +Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Eric P Xing +
    + ATC 2017 + + +
    + + [code] + + + [project] + +

    +
    + +
    +

    + Recurrent Topic-transition GAN for Visual Paragraph Generation
    + +Xiaodan Liang, Zhiting Hu, Hao Zhang, Chuang Gan, Eric P Xing +
    + ICCV 2017 + + +
    + + +

    +
    + +

     

    +

    2016

    +
    +

    + On the Reducibility of Submodular Functions
    + +Jincheng Mei, Hao Zhang, Bao-Liang Lu +
    + AISTATS 2016 + + +
    + + +

    +
    + +
    +

    + Geeps: Scalable Deep Learning on Distributed GPUs with a GPU-specialized Parameter Server
    + +Henggang Cui, Hao Zhang, Gregory R Ganger, Phillip B Gibbons, Eric P Xing +
    + EUROSYS 2016 + + +
    + + [code] + + +

    +
    + +
    +

    + Combining the Best of Convolutional Layers and Recurrent Layers: A Hybrid Network for Semantic Segmentation
    + +Zhicheng Yan, Hao Zhang, Yangqing Jia, Thomas Breuel, Yizhou Yu +
    + Preprint 2016 + + +
    + + +

    +
    + +
    +

    + Learning Concept Taxonomies from Multi-modal Data
    + +Hao Zhang, Zhiting Hu, Yuntian Deng, Mrinmaya Sachan, Zhicheng Yan, Eric P. Xing +
    + ACL 2016 + + +
    + + +

    +
    + +

     

    +

    2015

    +
    +

    + Automatic Photo Adjustment Using Deep Neural Networks
    + +Zhicheng Yan, Hao Zhang, Baoyuan Wang, Sylvain Paris, Yizhou Yu +
    + ACM Transactions on Graphics 2015 + + +
    + + [code] + + +

    +
    + +
    +

    + Dynamic Topic Modeling for Monitoring Market Competition from Online Text and Image Data
    + +Hao Zhang, Gunhee Kim, Eric P Xing +
    + KDD 2015 + + +
    + + + [project] + +

    +
    + +
    +

    + A Boosting-Based Spatial-Spectral Model for Stroke Patients' EEG Analysis in Rehabilitation Training
    + +Ye Liu, Hao Zhang, Min Chen, Liqing Zhang +
    + Transactions on Neural Systems and Rehabilitation Engineering 2015 + + +
    + + +

    +
    + +
    +

    + HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition
    + +Zhicheng Yan, Hao Zhang, Robinson Piramuthu, Vignesh Jagadeesh, Dennis DeCoste, Wei Di, Yizhou Yu +
    + ICCV 2015 + + +
    + + [code] + + +

    +
    + +

     

    +

    2014

    +
    +

    + A Tensor-based Scheme for Stroke Patients’ Motor Imagery EEG Analysis in BCI-FES Rehabilitation Training
    + +Ye Liu, Mingfen Li, Hao Zhang, Hang Wang, Junhua Li, Jie Jia, Yi Wu, Liqing Zhang +
    + Journal of neuroscience methods 2014 + + +
    + + +

    +
    + +
    +

    + Common Spatial-spectral Boosting Pattern for Brain-computer Interface
    + +Ye Liu, Hao Zhang, Qibin Zhao, Liqing Zhang +
    + ECAI 2014 + + +
    + + +

    +
    + +

     

    +

    2013

    +
    +

    + Gaussian Mixture Modeling in Stroke Patients' Rehabilitation EEG Data Analysis
    + +Hao Zhang, Ye Liu, Jianyi Liang, Jianting Cao, Liqing Zhang +
    + EMBC 2013 + + +
    + + +

    +
    + +
    +

    + Single-trial Discrimination of EEG Signals for Stroke Patients: a General Multi-way Analysis
    + +Ye Liu, Mingfen Li, Hao Zhang, Junhua Li, Jie Jia, Yi Wu, Jianting Cao, Liqing Zhang +
    + EMBC 2013 + + +
    + +

    diff --git a/publications.json b/publications.json new file mode 100644 index 0000000..ec3760b --- /dev/null +++ b/publications.json @@ -0,0 +1,567 @@ +[ + { + "title": "CLLMs: Consistency Large Language Models", + "authors": "Siqi Kou*, Lanxiang Hu*, Zhezhi He, Zhijie Deng, Hao Zhang", + "venue": "Preprint 2024", + "pdf": "https://arxiv.org/pdf/2403.00835.pdf", + "code": "https://github.com/hao-ai-lab/Consistency_LLM", + "presentation": "", + "award": "", + "project": "", + "tag": "Selected, Large Language Models, Scalable ML, ML Systems", + "date": "03/2024" + }, + { + "title": "DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving", + "authors": "Yinmin Zhong, Shengyu Liu, Junda Chen, Jianbo Hu, Yibo Zhu, Xuanzhe Liu, Xin Jin, Hao Zhang", + "venue": "Preprint 2024", + "pdf": "https://arxiv.org/pdf/2401.09670v1.pdf", + "code": "", + "presentation": "", + "award": "", + "project": "", + "tag": "Selected, Large Language Models, ML Systems", + "date": "01/2024" + }, + { + "title": "Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference", + "authors": "Wei-Lin Chiang*, Lianmin Zheng*, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Banghua Zhu, Hao Zhang, Michael Jordan, Joseph E. Gonzalez, Ion Stoica", + "venue": "Preprint 2024", + "pdf": "https://arxiv.org/pdf/2403.04132.pdf", + "code": "https://github.com/lm-sys/FastChat", + "presentation": "", + "award": "", + "project": "https://chat.lmsys.org/", + "tag": "Selected, Large Language Models", + "date": "03/2024" + }, + { + "title": "APIServe: Efficient API Support for Large-Language Model Inferencing", + "authors": "Reyna Abhyankar*, Zijian He*, Vikranth Srivatsa, Hao Zhang, Yiying Zhang", + "venue": "Preprint 2024", + "pdf": "https://arxiv.org/pdf/2402.01869.pdf", + "code": "", + "presentation": "", + "award": "", + "project": "", + "tag": "Selected, Large Language Models, ML Systems", + "date": "02/2024" + }, + { + "title": "Break the Sequential Dependency of LLM Inference using Lookahead Decoding", + "authors": "Yichao Fu, Peter Bailis, Ion Stoica, Hao Zhang", + "venue": "Preprint 2024", + "pdf": "https://arxiv.org/pdf/2402.02057v1.pdf", + "code": "https://github.com/hao-ai-lab/LookaheadDecoding", + 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