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cs.CL2026
Real Images, Worse Judgments: Evaluating Vision-Language Models on Concreteness and Imagery
Yifan Jiang, Ruoxi Ning, Sheng Yao +1
Visual inputs are often assumed to improve language understanding in multimodal models. We examine this assumption by asking whether vision-language models (VLMs) can distinguish u…
cs.CL2026
Chartographer: Counterfactual Chart Generation for Evaluating Vision-Language Models
Yifan Jiang, Dae Yon Hwang, Jesse C. Cresswell +1
Chart question-answering (QA) benchmarks aim to pose questions that require visual reasoning to correctly answer, but vision-language models (VLMs) can often reach solutions throug…
cs.CL2022
Testing Pre-trained Language Models' Understanding of Distributivity via Causal Mediation Analysis
Pangbo Ban, Yifan Jiang, Tianran Liu +1
To what extent do pre-trained language models grasp semantic knowledge regarding the phenomenon of distributivity? In this paper, we introduce DistNLI, a new diagnostic dataset for…