collaborators

14 papers

cs.AI2026

Isotropy Cliffs: The Geometric Signature of Decision-Making in Large Language Models

Okan S. Coskun, Florian Rottach, Carsten Eickhoff +1

We investigate the geometry of decision-making in Multiple Choice Question Answering (MCQA) through the lens of isotropy. Analyzing five open-weight models across diverse datasets,…

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.AI2026

VESTA: Visual Exploration with Statistical Tool Agents

William Rudman, Abhishek Divekar, Kanishk Jain +6

Fitting quantitative models to data is a central step in scientific workflows, yet it remains one of the least automated. Recent agent-based systems leverage language and vision-la…

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.CV2026

Mechanisms of Prompt-Induced Hallucination in Vision-Language Models

William Rudman, Michal Golovanevsky, Dana Arad +4

Large vision-language models (VLMs) are highly capable, yet often hallucinate by favoring textual prompts over visual evidence. We study this failure mode in a controlled object-co…