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cs.CL2026

Vision-Default, Prior-Override: Causal Mechanisms of Perception-Knowledge Conflict in Vision-Language Models

Niclas Lietzow, Danielle Bitterman, Carsten Eickhoff +2

Vision-language models must reconcile visual evidence with memorized world knowledge when the two conflict. How they resolve this conflict shapes the reliability of multimodal syst…

cs.CL2026

What's in a Name? Morphological Shortcuts by LLMs in Pharmacology

Kaijie Mo, Thomas Yang, Chantal Shaib +6

The morphological form of a word can often give cues to its meaning, but purely relying on these mappings can lead to overgeneralization in high-stakes domains. In the medical doma…

cs.CL2026

Multimodal QUD: Inquisitive Questions from Scientific Figures

Yating Wu, William Rudman, Venkata S Govindarajan +2

Discourse comprehension in complex documents often involves continuously posing and resolving Questions Under Discussion (QUDs). While QUD frameworks have so far focused on text, s…

cs.CL2026

When to Call an Apple Red: Humans Follow Introspective Rules, VLMs Don't

Jonathan Nemitz, Carsten Eickhoff, Junyi Jessy Li +3

Understanding when Vision-Language Models (VLMs) will behave unexpectedly, whether models can reliably predict their own behavior, and if models adhere to their introspective reaso…

cs.CL2025

TRIM: Achieving Extreme Sparsity with Targeted Row-wise Iterative Metric-driven Pruning

Florentin Beck, William Rudman, Carsten Eickhoff

Large Language Models (LLMs) present significant computational and memory challenges due to their extensive size, making pruning essential for their efficient deployment. Existing…

cs.CL2025

What Do VLMs NOTICE? A Mechanistic Interpretability Pipeline for Gaussian-Noise-free Text-Image Corruption and Evaluation

Michal Golovanevsky, William Rudman, Vedant Palit +2

Vision-Language Models (VLMs) have gained community-spanning prominence due to their ability to integrate visual and textual inputs to perform complex tasks. Despite their success,…