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Marie-Francine Moens

ACL 2026×2效率与系统评测与基准多模态推理
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0 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #3/4ACL 2026Poster· Natural Language Processing

Protecting multimodal large language models against misleading visualizations

Jonathan Tonglet · Tinne Tuytelaars · Marie-Francine Moens · Iryna Gurevych

摘要

Visualizations play a pivotal role in daily communication in an increasingly data-driven world. Research on multimodal large language models (MLLMs) for automated chart understanding has accelerated massively, with steady improvements on standard benchmarks. However, for MLLMs to be reliable, the...

多模态效率与系统评测与基准OpenReview 项目页
作者位次 #4/4ACL 2026Findings· Findings of ACL

C limate C ause: Complex and Implicit Causal Structures in Climate Reports

Liesbeth Allein · Nataly Pineda-Castañeda · Andrea Rocci · Marie-Francine Moens

摘要

Understanding climate change requires reasoning over complex causal networks. Yet, existing causal discovery datasets predominantly capture explicit, direct causal relations. We introduce ClimateCause, a manually expert-annotated dataset of higher-order causal structures from science-for-policy c...

推理效率与系统评测与基准OpenReview 项目页

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