collaborators

8 papers

cs.CV2026

ZeroBench: An Impossible Visual Benchmark for Contemporary Large Multimodal Models

Jonathan Roberts, Mohammad Reza Taesiri, Ansh Sharma +31

Large Multimodal Models (LMMs) exhibit shortfalls when interpreting images and, by some measures, have poorer spatial cognition than young children or animals. Despite this, they a…

cs.CL2026

HoT: Highlighted Chain of Thought for Referencing Supporting Facts from Inputs

Tin Nguyen, Logan Bolton, Mohammad Reza Taesiri +2

An Achilles heel of Large Language Models (LLMs) is their tendency to hallucinate non-factual statements. A response mixed of factual and non-factual statements poses a challenge f…

cs.CV2026

CodeCytos: AI-assisted spatial molecular imaging analysis via code-augmented agent action space

Hung Q. Vo, Huy Q. Vo, Son T. Ly +6

Conventional tissue image analysis software provides foundational capabilities for cellular analysis, including segmentation, basic morphological feature extraction, and spatial or…

cs.CV2026

SketchVLM: Vision language models can annotate images to explain thoughts and guide users

Brandon Collins, Logan Bolton, Hung Huy Nguyen +3

When answering questions about images, humans naturally point, label, and draw to explain their reasoning. In contrast, modern vision-language models (VLMs) such as Gemini-3-Pro an…

cs.LG2026

Vision Language Models are Biased

An Vo, Khai-Nguyen Nguyen, Mohammad Reza Taesiri +3

Large language models (LLMs) memorize a vast amount of prior knowledge from the Internet that helps them on downstream tasks but also may notoriously sway their outputs towards wro…

cs.CV2025

Understanding Generative AI Capabilities in Everyday Image Editing Tasks

Mohammad Reza Taesiri, Brandon Collins, Logan Bolton +4

Generative AI (GenAI) holds significant promise for automating everyday image editing tasks, especially following the recent release of GPT-4o on March 25, 2025. However, what subj…