activity
20242026
collaborators
Showing 2025Show all

7 papers · 1 filter

cs.CV2025

Infinity and Beyond: Compositional Alignment in VAR and Diffusion T2I Models

Hossein Shahabadi, Niki Sepasian, Arash Marioriyad +2

Achieving compositional alignment between textual descriptions and generated images - covering objects, attributes, and spatial relationships - remains a core challenge for modern…

cs.CL2025

The Silent Judge: Unacknowledged Shortcut Bias in LLM-as-a-Judge

Arash Marioriyad, Mohammad Hossein Rohban, Mahdieh Soleymani Baghshah

Large language models (LLMs) are increasingly deployed as automatic judges to evaluate system outputs in tasks such as summarization, dialogue, and creative writing. A faithful jud…

cs.CL2025

Unspoken Hints: Accuracy Without Acknowledgement in LLM Reasoning

Arash Marioriyad, Shaygan Adim, Nima Alighardashi +2

Large language models (LLMs) increasingly rely on chain-of-thought (CoT) prompting to solve mathematical and logical reasoning tasks. Yet, a central question remains: to what exten…

cs.CV2025

No Concept Left Behind: Test-Time Optimization for Compositional Text-to-Image Generation

Mohammad Hossein Sameti, Amir M. Mansourian, Arash Marioriyad +3

Despite recent advances in text-to-image (T2I) models, they often fail to faithfully render all elements of complex prompts, frequently omitting or misrepresenting specific objects…

cs.CV2025

Evaluating the Evaluators: Metrics for Compositional Text-to-Image Generation

Seyed Amir Kasaei, Ali Aghayari, Arash Marioriyad +4

Text-image generation has advanced rapidly, but assessing whether outputs truly capture the objects, attributes, and relations described in prompts remains a central challenge. Eva…

cs.CV2025

CARINOX: Inference-time Scaling with Category-Aware Reward-based Initial Noise Optimization and Exploration

Seyed Amir Kasaei, Ali Aghayari, Arash Marioriyad +5

Text-to-image diffusion models, such as Stable Diffusion, can produce high-quality and diverse images but often fail to achieve compositional alignment, particularly when prompts d…

cs.CV2025

Why Settle for Mid: A Probabilistic Viewpoint to Spatial Relationship Alignment in Text-to-image Models

Parham Rezaei, Arash Marioriyad, Mahdieh Soleymani Baghshah +1

Despite the ability of text-to-image models to generate high-quality, realistic, and diverse images, they face challenges in compositional generation, often struggling to accuratel…