13 papers
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…
Hidden Meanings in Plain Sight: RebusBench for Evaluating Cognitive Visual Reasoning
Seyed Amir Kasaei, Arash Marioriyad, Mahbod Khaleti +3
Large Vision-Language Models (LVLMs) have achieved remarkable proficiency in explicit visual recognition, effectively describing what is directly visible in an image. However, a cr…
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…
Lying to Win: Assessing LLM Deception through Human-AI Games and Parallel-World Probing
Arash Marioriyad, Ali Nouri, Mohammad Hossein Rohban +1
As Large Language Models (LLMs) transition into autonomous agentic roles, the risk of deception-defined behaviorally as the systematic provision of false information to satisfy ext…
The Judge Who Never Admits: Hidden Shortcuts in LLM-based Evaluation
Arash Marioriyad, Omid Ghahroodi, Ehsaneddin Asgari +2
Large language models (LLMs) are increasingly used as automatic judges to evaluate system outputs in tasks such as reasoning, question answering, and creative writing. A faithful j…
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…