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Qi Shi

ACL 2026×2AAAI 2026ECCV 2026多模态可解释性智能体与工具评测与基准检索与知识
新星分贡献者
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核心/参与15
方向广度16
合作网络12
0 一作 · 4 篇 · ACL 2026 / AAAI 2026 / ECCV 2026

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2026 顶会论文

4
作者位次 #12/22ECCV 2026Poster

Cheers: Decoupling Patch Details from Semantic Representations Enables Unified Multimodal Comprehension and Generation

Yichen Zhang · Da Peng · Zonghao Guo · zijian zhang · Xuesong Yang · Tong Sun · Shichu Sun · Yidan Zhang · Yanghao Li · Haiyan Zhao · Wang Xu · Qi Shi · Yangang Sun · Chi Chen · Shuo Wang · Yukun Yan · Xu Han · Qiang Ma · Wei Ke · Liang Wang · Zhiyuan Liu · Maosong Sun

多模态可解释性Image Generation, Editing & DiffusionOpenReview
作者位次 #4/10ACL 2026Poster· Natural Language Processing

A uto R eproduce: Automatic AI Experiment Reproduction with Paper Lineage

Xuanle Zhao · Zilin Sang · Yuxuan Li · Qi Shi · Weilun Zhao · Shuo Wang · Duzhen Zhang · Xu Han · Zhiyuan Liu · Maosong Sun

摘要

Efficient reproduction of research papers is pivotal to accelerating scientific progress. However, the increasing complexity of proposed methods often renders reproduction a labor-intensive endeavor, necessitating profound domain expertise.To address this, we introduce the paper lineage, which sy...

智能体与工具评测与基准检索与知识OpenReview 项目页
作者位次 #9/11ACL 2026Findings· Findings of ACL

A uto V ec C oder: Teaching LLM s to Generate Explicitly Vectorized Code

ShangZhan Li · Xinyu Yin · Xuanyu Jin · Ye He · Yuxin Zhou · Yuxuan Li · Xu Han · Wanxiang Che · Qi Shi · Ting Liu · Maosong Sun

摘要

Vectorization via Single Instruction, Multiple Data (SIMD) architectures is a cornerstone of high-performance computing. To fully exploit hardware potential, developers often resort to explicit vectorization using intrinsics, as compiler-based auto-vectorization frequently yields suboptimal resul...

代码对齐与偏好强化学习与后训练OpenReview 项目页
作者位次 #4/4AAAI 2026Poster· Artificial Intelligence

TRACE: Trajectory-based Activation Change Estimation for Task-specific Data Selection

Ye He · ShangZhan Li · Yuxin Zhou · Qi Shi

数据与预训练OpenReview

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