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20222026
most citedForgotten Polygons: Multimodal Large Language Models are Shape-Blind

2 citations · 6 across the 18 of their papers we have counts for

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10 papers · 1 filter

astro-ph.GA2026

Large dust grains escaping from a supernova remnant

Evgenii O. Vasiliev

Dust grains produced in the supernova (SN) ejecta at early ages are partially destroyed in hot gas of the SN remnant. Large grains owing to their inertia can overtake the forward s…

cs.LG2026

Mol-JEPA: A multimodal Joint Embedding Predictive Architecture for Molecules

Florian Rottach, Sebastian Schieferdecker, William Rudman +2

Despite recent advances in molecular foundation models, several limitations remain, such as chemically invalid augmentations, modality collapse, and incomplete representation of bi…

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.CV2026

Is There Knowledge Left to Extract? Evidence of Fragility in Medically Fine-Tuned Vision-Language Models

Oliver McLaughlin, Daniel Shubin, Carsten Eickhoff +3

Vision-language models (VLMs) are increasingly adapted through domain-specific fine-tuning, yet it remains unclear whether this improves reasoning beyond superficial visual cues, p…

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.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…