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Zhou Liu

ACL 2026×4NeurIPS 2026多模态评测与基准推理智能体与工具强化学习与后训练
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0 一作 · 5 篇 · ACL 2026 / NeurIPS 2026

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2026 顶会论文

5
作者位次 #2/3NeurIPS 2026Poster

Slide P2V-Bench: A Cross-Domain Benchmark for Slide-Centric Scientific Paper-to-Presentation Video Generation

Ligang Huang · Zhou Liu · Wentao Zhang

多模态评测与基准OpenReview
作者位次 #3/5ACL 2026Poster· Natural Language Processing

S ci F low-Bench: Evaluating Structure-Aware Scientific Diagram Generation via Inverse Parsing

Tong Zhang · honglin lin · Zhou Liu · an Jiaotong University) · Wentao Zhang

摘要

Scientific diagrams convey explicit structural information, yet modern text-to-image models often produce visually plausible but structurally incorrect results. Existing benchmarks either rely on image-centric or subjective metrics insensitive to structure, or evaluate intermediate symbolic repre...

推理智能体与工具多模态OpenReview 项目页
作者位次 #2/6ACL 2026Poster· Natural Language Processing

U ni D ata B ench: Evaluating Data Analytics Agents Across Structured and Unstructured Data

Han Weng · Zhou Liu · Yuanfeng SONG · Xiaoming Yin · Xing Chen · Wentao Zhang

摘要

In real-world business environments, data is stored in a variety of sources, including structured relational databases, semi-structured databases, and unstructured files. The ability to extract reasonable insights across these diverse sources is integral to data-driven decision-making. Existing b...

评测与基准推理智能体与工具OpenReview 项目页
作者位次 #3/10ACL 2026Findings· Findings of ACL

Reinforcement Learning with Semantic Rewards Enables Low-Resource Language Expansion without Alignment Tax

Zeli Su · Ziyin Zhang · Zhou Liu · Xuexian Song · Zhankai Xu · Longfei Zheng · Xiaolu Zhang · Rong Fu · Guixian Xu · Wentao Zhang

摘要

Extending large language models (LLMs) to low-resource languages often incurs an “align- ment tax”: improvements in the target lan- guage come at the cost of catastrophic forget- ting in general capabilities. We argue that this trade-off arises from the rigidity of supervised fine-tuning (SFT), w...

强化学习与后训练对齐与偏好多语言与语言学OpenReview 项目页
作者位次 #5/6ACL 2026Findings· Findings of ACL

L ong I nsight B ench: A Comprehensive Benchmark for Evaluating Omni-Modal Models on Human-Centric Long-Video Understanding.

ZhaoYang Han · Qihan Lin · Hao Liang · Bowen Chen · Zhou Liu · Wentao Zhang

摘要

We introduce \textbf{LongInsightBench} , the first benchmark designed to assess models’ ability to understand long videos, with a focus on human language, viewpoints, actions, and other contextual elements, while integrating \textbf{visual, audio, and text} modalities. Our benchmark excels in thr...

多模态评测与基准数据与预训练OpenReview 项目页

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