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Mao Yang

ICLR 2026×4ACL 2026×2HPCA 2026MICRO 2026PPoPP 2026VLDB 2026推理长上下文与架构代码效率与系统强化学习与后训练
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0 一作 · 10 篇 · ICLR 2026 / ACL 2026 / HPCA 2026 / MICRO 2026 / PPoPP 2026 / VLDB 2026

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2026 顶会论文

10
作者位次 #5/5MICRO 2026Oral· GPU Microarchitecture & Numerical Precision

Bit-Accurate Modeling of GPU Matrix Multiply-Accumulate Units: Demystifying Numerical Discrepancy and Accuracy

Peichen Xie · Shuotao Xu · Yang Wang · Fan Yang · Mao Yang

长上下文与架构OpenReview
作者位次 #9/9ACL 2026Poster· Natural Language Processing

Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training

Kailai Yang · Xiao Liu · Lei Ji · Hao Li · Xiao Liang · Zhiwei Liu · Yeyun Gong · Peng CHENG · Mao Yang

摘要

Continual pre-training on small-scale task-specific data is an effective method for improving large language models in new target fields, yet it risks catastrophic forgetting of their original capabilities. A common solution is to re-weight training data mixtures from source and target fields on...

推理评测与基准数据与预训练OpenReview 项目页
作者位次 #8/10ACL 2026Poster· Natural Language Processing

Gold-Medal-Level Olympiad Geometry Solving with Efficient Heuristic Auxiliary Constructions

Boyan Duan · Xiao Liang · Shuai Lu · Yaoxiang Wang · yelong shen · Kai-Wei Chang · Ying Nian Wu · Mao Yang · Weizhu Chen · Yeyun Gong

摘要

Automated theorem proving in Euclidean geometry, particularly for International Mathematical Olympiad (IMO) level problems, remains a major challenge and an important research focus in Artificial Intelligence. In this paper, we present a highly efficient method for geometry theorem proving that r...

效率与系统评测与基准推理OpenReview 项目页

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