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20242026
most citedKhayyam Challenge (PersianMMLU): Is Your LLM Truly Wise to The Persian Language?

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

ORCA: Hunting Compositional Failures in Text-to-Image Diffusion

Arshia Hemmat, Amirhossein Vahidi, Amitis Shidani +4

Text-to-image diffusion models fail predictably on compositional prompts: attributes bind to the wrong objects, spatial relations invert, and multi-object scenes lose count. Recent…

cs.LG2026

Shortest-Path Flow Matching with Mixture-Conditioned Bases for OOD Generalization to Unseen Conditions

Andrea Rubbi, Amir Akbarnejad, Mohammad Vali Sanian +10

Robust generalization under distribution shift remains a key challenge for conditional generative modeling: conditional flow-based methods often fit the training conditions well bu…

cs.CV2025

SIGMMA: Hierarchical Graph-Based Multi-Scale Multi-modal Contrastive Alignment of Histopathology Image and Spatial Transcriptome

Dabin Jeong, Amirhossein Vahidi, Ciro Ramírez-Suástegui +11

Recent advances in computational pathology have leveraged vision-language models to learn joint representations of Hematoxylin and Eosin (HE) images with spatial transcriptomic (ST…

cs.CV2025

CHAMMI-75: Pre-training multi-channel models with heterogeneous microscopy images

Vidit Agrawal, John Peters, Tyler N. Thompson +13

Quantifying cell morphology using images and machine learning has proven to be a powerful tool to study the response of cells to treatments. However, models used to quantify cellul…

cs.CV2025

3D-Guided Scalable Flow Matching for Generating Volumetric Tissue Spatial Transcriptomics from Serial Histology

Mohammad Vali Sanian, Arshia Hemmat, Amirhossein Vahidi +9

A scalable and robust 3D tissue transcriptomics profile can enable a holistic understanding of tissue organization and provide deeper insights into human biology and disease. Most…

cs.AI2025

MEENA (PersianMMMU): Multimodal-Multilingual Educational Exams for N-level Assessment

Omid Ghahroodi, Arshia Hemmat, Marzia Nouri +8

Recent advancements in large vision-language models (VLMs) have primarily focused on English, with limited attention given to other languages. To address this gap, we introduce MEE…

cs.CL2024★ 1 cited

Khayyam Challenge (PersianMMLU): Is Your LLM Truly Wise to The Persian Language?

Omid Ghahroodi, Marzia Nouri, Mohammad Vali Sanian +5

Evaluating Large Language Models (LLMs) is challenging due to their generative nature, necessitating precise evaluation methodologies. Additionally, non-English LLM evaluation lags…