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Chao Zhang

SIGIR 2026×2AAAI 2026OSDI 2026检索与知识可解释性多模态强化学习与后训练效率与系统
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0 一作 · 4 篇 · SIGIR 2026 / AAAI 2026 / OSDI 2026

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2026 顶会论文

4
作者位次 #5/13OSDI 2026Oral· Operating Systems & Distributed Systems

M3U: Scalable Kernel Memory Management for Efficient Post-Copy Live Migration of High-End Virtual Machines

Yizhe Xu · Yuan Tao · Zhibin Zhang · Kang Yan · Chao Zhang · Shuo Shi · Zongpu Zhang · Xu Huan · Yibin Shen · Xudong Zheng · Jiesheng Wu · Jian Li · Haibing Guan

摘要

High-end virtual machines (VMs) have become essential in public clouds for supporting large-scale guest applications. While conventional pre-copy live migration cannot reliably migrate such high-end VMs due to convergence problems, post-copy migration offers a viable alternative. However, high-en...

效率与系统评测与基准检索与知识OpenReview
作者位次 #5/12SIGIR 2026Oral· Information Retrieval (Full)

ProEchoMem: Enhancing Long Video Understanding via Multi-Trace Probe-Echo Memory

Derong Xu · Yanxin Chen · an Jiaotong University) · an Jiaotong University) · Chao Zhang · Maolin WANG · Yiqi Wang · Jipeng Qiang · Xuetao Wei · Hongzhi Yin · an Jiaotong University) · an Jiaotong University)

摘要

Large vision-language models (LVLMs) have shown significant progress in video understanding, but they struggle to scale to long videos due to limited context windows. Existing methods reduce input dimensionality via frame sampling and feature compression, yet discard details and incur high comput...

检索与知识可解释性多模态OpenReview
作者位次 #7/9SIGIR 2026Poster· Information Retrieval (Industry)

SIGMA: A Semantic-Grounded Instruction-Driven Generative Multi-Task Recommender at AliExpress

Yang Yu · Lei Kou · Huaikuan Yi · Bin Chen · Yayu Cao · Lei Shen · Chao Zhang · Bing Wang · Xiaoyi Zeng

摘要

With the rapid evolution of Large Language Models (LLMs), generative recommendation is gradually reshaping the paradigm of recommender systems. However, most existing methods remain confined to the interaction-driven next-item prediction paradigm, struggling to keep pace with the latest evolving...

数据与预训练可解释性强化学习与后训练OpenReview

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