Using Perspectival Words Is Harder Than Vocabulary Words for Humans —and Even More So for Multimodal Language Models
Dota Tianai Dong Max Planck Institute for Psycholinguistics, Yifan Luo, Po-Ya Angela Wang National Taiwan University, Asli Ozyurek mpi for psycholinguistics, Paula Rubio-Fernandez The Max Planck Institute for Psycholinguistics
Multimodal language models (MLMs) increasingly demonstrate human-like communication, yet their use of everyday perspectival words remains poorly understood. To address this gap, we compare humans and MLMs in their use of three word types, which we predict impose increasing cognitive demands: vocabulary (e.g., ’boat’ or ’cup’), possessives (e.g., ’mine’ vs. ’yours’), and demonstratives (e.g., ’this one’ vs. ’that one’). Testing seven MLMs against human participants, we find that perspectival words are harder than vocabulary words for both groups. The gap is even larger for MLMs: while models approach human-level performance on using vocabulary, they exhibit clear deficits with possessives and even greater difficulties with demonstratives. Ablation analyses point to limitations in perspective-taking and spatial reasoning as key sources of these gaps in MLMs. Instruction-based prompting helps close the gap for possessives but still leaves demonstratives far below human performance. These results show that, unlike vocabulary, perspectival words pose a greater challenge in human communication—and this difficulty is further amplified in MLMs, revealing a crucial shortfall in their pragmatic and social-cognitive abilities.
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Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · 2026 · 正式发表