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Yulong Ao

ACL 2026×2ECCV 2026多模态检索与知识效率与系统推理强化学习与后训练
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合作网络6
0 一作 · 3 篇 · ACL 2026 / ECCV 2026

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2026 顶会论文

3
作者位次 #6/7ECCV 2026Poster

Think While Watching: Online Streaming Segment-Level Memory for Multi-Turn Video Reasoning in Multimodal Large Language Models

Lu Wang · Zhuoran Jin · Yupu Hao · Yubo Chen · Kang Liu · Yulong Ao · Jun Zhao

多模态推理检索与知识Video Understanding, Generation and Multimodal LearningOpenReview
作者位次 #4/5ACL 2026Poster· Natural Language Processing

PDT rim: Targeted Pruning for Prefill-Decode Disaggregation in Inference

Hao Zhang · Lyu Mengsi · Zhuo Chen · Yulong Ao · Yonghua Lin

摘要

Large Language Models (LLMs) demonstrate exceptional capabilities across various tasks, but their deployment is constrained by high computational and memory costs. Model pruning provides an effective means to alleviate these demands. However, existing methods often ignore the characteristics of p...

效率与系统强化学习与后训练检索与知识OpenReview 项目页
作者位次 #4/5ACL 2026Findings· Findings of ACL

T rim T okenator: Towards Adaptive Visual Token Pruning for Large Multimodal Models

Hao Zhang · Lyu Mengsi · Chenrui He · Yulong Ao · Yonghua Lin

摘要

Large Multimodal Models (LMMs) have achieved significant success across various tasks. These models usually encode visual inputs into dense token sequences, which are then concatenated with textual tokens and jointly processed by a language model. However, the increased token count substantially...

效率与系统多模态对齐与偏好OpenReview 项目页

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