Xin Liu

According to our database, Xin Liu authored at least 49 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

veScale-FSDP: Flexible and High-Performance FSDP at Scale.

Zezhou Wang, Youjie Li, Zhiqi Lin, Jiacheng Yang, Cong Xie, Guanyu Feng, Zheng Zhong, Ziyue Huang, Hongyu Zhu, Zhi Zhang, Yanghua Peng, Xin Liu

CoRR, February, 2026

DASH: Deterministic Attention Scheduling for High-throughput Reproducible LLM Training.

Xinwei Qiang, Hongmin Chen, Shixuan Sun, Jingwen Leng, Xin Liu, Minyi Guo

CoRR, January, 2026

MegaScale-Omni: A Hyper-Scale, Workload-Resilient System for MultiModal LLM Training in Production.

Chunyu Xue, Yangrui Chen, Jianyu Jiang, Ningxin Zheng, Junda Feng, Jingji Chen, Shixiong Zhao, Shen Yan, Yi Lin, Lei Shi, Zanbo Wang, Lishu Luo, Faming Wu, Haibin Lin, Yanghua Peng, Xin Liu, Quan Chen

Proceedings of the 21st European Conference on Computer Systems, 2026

Laminar: A Scalable Asynchronous RL Post-Training Framework.

Guangming Sheng, Yuxuan Tong, Borui Wan, Wang Zhang, Chaobo Jia, Xibin Wu, Yuqi Wu, Xiang Li, Chi Zhang, Yanghua Peng, Haibin Lin, Xin Liu, Chuan Wu

Proceedings of the 21st European Conference on Computer Systems, 2026

MegaScale-MoE: Large-Scale Communication-Efficient Training of Mixture-of-Experts Models in Production.

Chao Jin, Ziheng Jiang, Zhihao Bai, Zheng Zhong, Juncai Liu, Xiang Li, Ningxin Zheng, Xi Wang, Cong Xie, Qi Huang, Wen Heng, Yiyuan Ma, Wenlei Bao, Size Zheng, Xuegui Zheng, Yanghua Peng, Haibin Lin, Xuanzhe Liu, Xin Jin, Xin Liu

Proceedings of the 21st European Conference on Computer Systems, 2026

SwiftSpec: Disaggregated Speculative Decoding and Fused Kernels for Low-Latency LLM Inference.

Ziyi Zhang, Ziheng Jiang, Chengquan Jiang, Menghan Yu, Size Zheng, Haibin Lin, Xin Liu, Henry Hoffmann

Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2026

OmniScale: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo.

Qianli Ma, Yaowei Zheng, Zhelun Shi, Zhongkai Zhao, Bin Jia, Ziyue Huang, Zhiqi Lin, Youjie Li, Jiacheng Yang, Yanghua Peng, Zhi Zhang, Xin Liu

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Cannikin: No Lagger of SLO in Concurrent Multiple LoRA LLM Serving.

Ruidong Zhu, Ziyue Jiang, Zhi Zhang, Xin Liu, Xuanzhe Liu, Xin Jin

IEEE Trans. Parallel Distributed Syst., September, 2025

VoxCPM: Tokenizer-Free TTS for Context-Aware Speech Generation and True-to-Life Voice Cloning.

Yixuan Zhou, Guoyang Zeng, Xin Liu, Xiang Li, Renjie Yu, Ziyang Wang, Runchuan Ye, Weiyue Sun, Jiancheng Gui, Kehan Li, Zhiyong Wu, Zhiyuan Liu

CoRR, September, 2025

Boosting Embodied AI Agents through Perception-Generation Disaggregation and Asynchronous Pipeline Execution.

Shulai Zhang, Ao Xu, Quan Chen, Han Zhao, Weihao Cui, Ningxin Zheng, Haibin Lin, Xin Liu, Minyi Guo

CoRR, September, 2025

LiquidGEMM: Hardware-Efficient W4A8 GEMM Kernel for High-Performance LLM Serving.

Huanqi Hu, Bowen Xiao, Shixuan Sun, Jianian Yin, Zhexi Zhang, Xiang Luo, Chengquan Jiang, Weiqi Xu, Xiaoying Jia, Xin Liu, Minyi Guo

CoRR, September, 2025

A Scalable Pipeline for Enabling Non-Verbal Speech Generation and Understanding.

Runchuan Ye, Yixuan Zhou, Renjie Yu, Zijian Lin, Kehan Li, Xiang Li, Xin Liu, Guoyang Zeng, Zhiyong Wu

CoRR, August, 2025

VeOmni: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo.

Qianli Ma, Yaowei Zheng, Zhelun Shi, Zhongkai Zhao, Bin Jia, Ziyue Huang, Zhiqi Lin, Youjie Li, Jiacheng Yang, Yanghua Peng, Zhi Zhang, Xin Liu

CoRR, August, 2025

SwiftSpec: Ultra-Low Latency LLM Decoding by Scaling Asynchronous Speculative Decoding.

Ziyi Zhang, Ziheng Jiang, Chengquan Jiang, Menghan Yu, Size Zheng, Haibin Lin, Henry Hoffmann, Xin Liu

CoRR, June, 2025

MegaScale-MoE: Large-Scale Communication-Efficient Training of Mixture-of-Experts Models in Production.

Chao Jin, Ziheng Jiang, Zhihao Bai, Zheng Zhong, Juncai Liu, Xiang Li, Ningxin Zheng, Xi Wang, Cong Xie, Qi Huang, Wen Heng, Yiyuan Ma, Wenlei Bao, Size Zheng, Yanghua Peng, Haibin Lin, Xuanzhe Liu, Xin Jin, Xin Liu

CoRR, May, 2025

Triton-distributed: Programming Overlapping Kernels on Distributed AI Systems with the Triton Compiler.

Size Zheng, Wenlei Bao, Qi Hou, Xuegui Zheng, Jin Fang, Chenhui Huang, Tianqi Li, Haojie Duanmu, Renze Chen, Ruifan Xu, Yifan Guo, Ningxin Zheng, Ziheng Jiang, Xinyi Di, Dongyang Wang, Jianxi Ye, Haibin Lin, Li-Wen Chang, Liqiang Lu, Yun Liang, Jidong Zhai, Xin Liu

CoRR, April, 2025

OVERLORD: Ultimate Scaling of DataLoader for Multi-Source Large Foundation Model Training.

Juntao Zhao, Qi Lu, Wei Jia, Borui Wan, Lei Zuo, Junda Feng, Jianyu Jiang, Yangrui Chen, Shuaishuai Cao, Jialing He, Kaihua Jiang, Yuanzhe Hu, Yanghua Peng, Haibin Lin, Xin Liu, Chuan Wu

CoRR, April, 2025

MegaScale-Infer: Serving Mixture-of-Experts at Scale with Disaggregated Expert Parallelism.

Ruidong Zhu, Ziheng Jiang, Chao Jin, Peng Wu, Cesar A. Stuardo, Dongyang Wang, Xinlei Zhang, Huaping Zhou, Haoran Wei, Yang Cheng, Jianzhe Xiao, Xinyi Zhang, Lingjun Liu, Haibin Lin, Li-Wen Chang, Jianxi Ye, Xiao Yu, Xuanzhe Liu, Xin Jin, Xin Liu

CoRR, April, 2025

ByteScale: Efficient Scaling of LLM Training with a 2048K Context Length on More Than 12,000 GPUs.

Hao Ge, Junda Feng, Qi Huang, Fangcheng Fu, Xiaonan Nie, Lei Zuo, Haibin Lin, Bin Cui, Xin Liu

CoRR, February, 2025

Robust LLM Training Infrastructure at ByteDance.

Borui Wan, Gaohong Liu, Zuquan Song, Jun Wang, Yun Zhang, Guangming Sheng, Shuguang Wang, Houmin Wei, Chenyuan Wang, Weiqiang Lou, Xi Yang, Mofan Zhang, Kaihua Jiang, Cheng Ren, Xiaoyun Zhi, Menghan Yu, Zhe Nan, Zhuolin Zheng, Baoquan Zhong, Qinlong Wang, Huan Yu, Jinxin Chi, Wang Zhang, Yuhan Li, Zixian Du, Sida Zhao, Yongqiang Zhang, Jingzhe Tang, Zherui Liu, Chuan Wu, Yanghua Peng, Haibin Lin, Wencong Xiao, Xin Liu, Liang Xiang

Proceedings of the ACM SIGOPS 31st Symposium on Operating Systems Principles, 2025

MegaScale-Infer: Efficient Mixture-of-Experts Model Serving with Disaggregated Expert Parallelism.

Ruidong Zhu, Ziheng Jiang, Chao Jin, Peng Wu, Cesar A. Stuardo, Dongyang Wang, Xinlei Zhang, Huaping Zhou, Haoran Wei, Yang Cheng, Jianzhe Xiao, Xinyi Zhang, Lingjun Liu, Haibin Lin, Li-Wen Chang, Jianxi Ye, Xiao Yu, Xuanzhe Liu, Xin Jin, Xin Liu

Proceedings of the ACM SIGCOMM 2025 Conference, 2025

ByteScale: Communication-Efficient Scaling of LLM Training with a 2048K Context Length on 16384 GPUs.

Hao Ge, Junda Feng, Qi Huang, Fangcheng Fu, Xiaonan Nie, Lei Zuo, Haibin Lin, Bin Cui, Xin Liu

Proceedings of the ACM SIGCOMM 2025 Conference, 2025

LiquidGEMM: Hardware-Efficient W4A8 GEMM Kernel for High-Performance LLM Serving.

Huanqi Hu, Bowen Xiao, Shixuan Sun, Jianian Yin, Zhexi Zhang, Xiang Luo, Chengquan Jiang, Weiqi Xu, Xiaoying Jia, Xin Liu, Minyi Guo

Proceedings of the International Conference for High Performance Computing, 2025

Understanding Stragglers in Large Model Training Using What-if Analysis.

Jinkun Lin, Ziheng Jiang, Zuquan Song, Sida Zhao, Menghan Yu, Zhanghan Wang, Chenyuan Wang, Zuocheng Shi, Xiang Shi, Wei Jia, Zherui Liu, Shuguang Wang, Haibin Lin, Xin Liu, Aurojit Panda, Jinyang Li

Proceedings of the 19th USENIX Symposium on Operating Systems Design and Implementation, 2025

ByteCheckpoint: A Unified Checkpointing System for Large Foundation Model Development.

Borui Wan, Mingji Han, Yiyao Sheng, Yanghua Peng, Haibin Lin, Mofan Zhang, Zhichao Lai, Menghan Yu, Junda Zhang, Zuquan Song, Xin Liu, Chuan Wu

Proceedings of the 22nd USENIX Symposium on Networked Systems Design and Implementation, 2025

COMET: Fine-grained Computation-communication Overlapping for Mixture-of-Experts.

Shulai Zhang, Ningxin Zheng, Haibin Lin, Ziheng Jiang, Wenlei Bao, Chengquan Jiang, Qi Hou, Weihao Cui, Size Zheng, Li-Wen Chang, Quan Chen, Xin Liu

Proceedings of the Eighth Conference on Machine Learning and Systems, 2025

TileLink: Generating Efficient Compute-Communication Overlapping Kernels using Tile-Centric Primitives.

Size Zheng, Jin Fang, Xuegui Zheng, Qi Hou, Wenlei Bao, Ningxin Zheng, Ziheng Jiang, Dongyang Wang, Jianxi Ye, Haibin Lin, Li-Wen Chang, Xin Liu

Proceedings of the Eighth Conference on Machine Learning and Systems, 2025

ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference.

Hanshi Sun, Li-Wen Chang, Wenlei Bao, Size Zheng, Ningxin Zheng, Xin Liu, Harry Dong, Yuejie Chi, Beidi Chen

Proceedings of the Forty-second International Conference on Machine Learning, 2025

A Comprehensive Overhaul of Multimodal Assistant with Small Language Models.

Minjie Zhu, Yichen Zhu, Ning Liu, Xin Liu, Zhiyuan Xu, Chaomin Shen, Yaxin Peng

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

ByteCheckpoint: A Unified Checkpointing System for LLM Development.

Borui Wan, Mingji Han, Yiyao Sheng, Zhichao Lai, Mofan Zhang, Junda Zhang, Yanghua Peng, Haibin Lin, Xin Liu, Chuan Wu

CoRR, 2024

MMRo: Are Multimodal LLMs Eligible as the Brain for In-Home Robotics?

Jinming Li, Yichen Zhu, Zhiyuan Xu, Jindong Gu, Minjie Zhu, Xin Liu, Ning Liu, Yaxin Peng, Feifei Feng, Jian Tang

CoRR, 2024

FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion.

Li-Wen Chang, Wenlei Bao, Qi Hou, Chengquan Jiang, Ningxin Zheng, Yinmin Zhong, Xuanrun Zhang, Zuquan Song, Ziheng Jiang, Haibin Lin, Xin Jin, Xin Liu

CoRR, 2024

RAGCache: Efficient Knowledge Caching for Retrieval-Augmented Generation.

Chao Jin, Zili Zhang, Xuanlin Jiang, Fangyue Liu, Xin Liu, Xuanzhe Liu, Xin Jin

CoRR, 2024

Mipha: A Comprehensive Overhaul of Multimodal Assistant with Small Language Models.

Minjie Zhu, Yichen Zhu, Xin Liu, Ning Liu, Zhiyuan Xu, Chaomin Shen, Yaxin Peng, Zhicai Ou, Feifei Feng, Jian Tang

CoRR, 2024

MuxFlow: efficient GPU sharing in production-level clusters with more than 10000 GPUs.

Xuanzhe Liu, Yihao Zhao, Shufan Liu, Xiang Li, Yibo Zhu, Xin Liu, Xin Jin

Sci. China Inf. Sci., 2024

MegaScale: Scaling Large Language Model Training to More Than 10, 000 GPUs.

Ziheng Jiang, Haibin Lin, Yinmin Zhong, Qi Huang, Yangrui Chen, Zhi Zhang, Yanghua Peng, Xiang Li, Cong Xie, Shibiao Nong, Yulu Jia, Sun He, Hongmin Chen, Zhihao Bai, Qi Hou, Shipeng Yan, Ding Zhou, Yiyao Sheng, Zhuo Jiang, Haohan Xu, Haoran Wei, Zhang Zhang, Pengfei Nie, Leqi Zou, Sida Zhao, Liang Xiang, Zherui Liu, Zhe Li, Xiaoying Jia, Jianxi Ye, Xin Jin, Xin Liu

Proceedings of the 21st USENIX Symposium on Networked Systems Design and Implementation, 2024

SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training.

Jinda Jia, Cong Xie, Hanlin Lu, Daoce Wang, Hao Feng, Chengming Zhang, Baixi Sun, Haibin Lin, Zhi Zhang, Xin Liu, Dingwen Tao

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Safety of Multimodal Large Language Models on Images and Text.

Xin Liu, Yichen Zhu, Yunshi Lan, Chao Yang, Yu Qiao

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models.

Xin Liu, Yichen Zhu, Jindong Gu, Yunshi Lan, Chao Yang, Yu Qiao

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Query-Relevant Images Jailbreak Large Multi-Modal Models.

Xin Liu, Yichen Zhu, Yunshi Lan, Chao Yang, Yu Qiao

CoRR, 2023

MuxFlow: Efficient and Safe GPU Sharing in Large-Scale Production Deep Learning Clusters.

Yihao Zhao, Xin Liu, Shufan Liu, Xiang Li, Yibo Zhu, Gang Huang, Xuanzhe Liu, Xin Jin

CoRR, 2023

vMF Loss: Exploring a Scattered Intra-class Hypersphere for Few-Shot Learning.

Xin Liu, Shijing Wang, Kairui Zhou, Yilin Lyu, Mingyang Song, Liping Jing, Tieyong Zeng, Jian Yu

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Not All Tasks Are Equal: A Parameter-Efficient Task Reweighting Method for Few-Shot Learning.

Xin Liu, Yilin Lyu, Liping Jing, Tieyong Zeng, Jian Yu

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Improving Zero-shot Visual Question Answering via Large Language Models with Reasoning Question Prompts.

Yunshi Lan, Xiang Li, Xin Liu, Yang Li, Wei Qin, Weining Qian

Proceedings of the 31st ACM International Conference on Multimedia, 2023

ByteTransformer: A High-Performance Transformer Boosted for Variable-Length Inputs.

Yujia Zhai, Chengquan Jiang, Leyuan Wang, Xiaoying Jia, Shang Zhang, Zizhong Chen, Xin Liu, Yibo Zhu

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

Recognizable Information Bottleneck.

Yilin Lyu, Xin Liu, Mingyang Song, Xinyue Wang, Yaxin Peng, Tieyong Zeng, Liping Jing

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

Adaptive distribution calibration for few-shot learning via optimal transport.

Xin Liu, Kairui Zhou, Pengbo Yang, Liping Jing, Jian Yu

Inf. Sci., 2022

BaGuaLu: targeting brain scale pretrained models with over 37 million cores.

Zixuan Ma, Jiaao He, Jiezhong Qiu, Huanqi Cao, Yuanwei Wang, Zhenbo Sun, Liyan Zheng, Haojie Wang, Shizhi Tang, Tianyu Zheng, Junyang Lin, Guanyu Feng, Zeqiang Huang, Jie Gao, Aohan Zeng, Jianwei Zhang, Runxin Zhong, Tianhui Shi, Sha Liu, Weimin Zheng, Jie Tang, Hongxia Yang, Xin Liu, Jidong Zhai, Wenguang Chen

Proceedings of the PPoPP '22: 27th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, Seoul, Republic of Korea, April 2, 2022

Teach Less, Learn More: On the Undistillable Classes in Knowledge Distillation.

Yichen Zhu, Ning Liu, Zhiyuan Xu, Xin Liu, Weibin Meng, Louis Wang, Zhicai Ou, Jian Tang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022