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Xuanle Zhao

ACL 2026×3AAAI 2026CVPR 2026ICLR 2026多模态强化学习与后训练推理代码智能体与工具
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一作贡献100
核心/参与29
方向广度19
合作网络12
3 一作 · 6 篇 · ACL 2026 / AAAI 2026 / CVPR 2026 / ICLR 2026

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2026 顶会论文

6
一作ACL 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 #2/5ACL 2026Findings· Findings of ACL

O mni D iagram: Advancing Unified Diagram Code Generation via Visual Interrogation Reward

Haoyue Yang · Xuanle Zhao · Xuexin Liu · Feibing Jiang · Yao Zhu

摘要

The paradigm of programmable diagram generation is evolving rapidly, playing a crucial role in structured visualization. However, most existing studies are confined to a narrow range of task formulations and language support, constraining their applicability to diverse diagram types. In this work...

强化学习与后训练代码推理OpenReview 项目页
一作ACL 2026Findings· Findings of ACL

C hem VLR : Prioritizing Reasoning in Perception for Chemical Vision-Language Understanding

Xuanle Zhao · Xinyuan Cai · Xiang Cheng · Xiuyi Chen · Bo XU

摘要

While Vision-Language Models (VLMs) have demonstrated significant potential in chemical visual understanding, current models are predominantly optimized for direct visual question-answering tasks. This paradigm often results in “black-box” systems that fail to utilize the inherent capability of L...

多模态可解释性推理OpenReview 项目页

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