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20232026
most citedFrom Pixels to Prose: A Large Dataset of Dense Image Captions

1 citations · 2 across the 8 of their papers we have counts for

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cs.CV2026

Flash-BoN: Instant Drafts for Inference-Time Scaling in Diffusion Models

Ruchit Rawal, Reza Shirkavand, Sayak Paul +5

Inference-time scaling for text-to-image generation has progressed from simple Best-of- (BoN) sampling to guided search methods that verify and steer candidate trajectories at i…

cs.CV2026

VGA-Bench: A Unified Benchmark and Multi-Model Framework for Video Aesthetics and Generation Quality Evaluation

Longteng Jiang, DanDan Zheng, Qianqian Qiao +7

The rapid advancement of AIGC-based video generation has underscored the critical need for comprehensive evaluation frameworks that go beyond traditional generation quality metrics…

cs.CV2025

ARGUS: Hallucination and Omission Evaluation in Video-LLMs

Ruchit Rawal, Reza Shirkavand, Heng Huang +2

Video large language models have not yet been widely deployed, largely due to their tendency to hallucinate. Typical benchmarks for Video-LLMs rely simply on multiple-choice questi…

cs.CV2024★ 1 cited

From Pixels to Prose: A Large Dataset of Dense Image Captions

Vasu Singla, Kaiyu Yue, Sukriti Paul +7

Training large vision-language models requires extensive, high-quality image-text pairs. Existing web-scraped datasets, however, are noisy and lack detailed image descriptions. To…

cs.CV2024

Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models

Alireza Ganjdanesh, Reza Shirkavand, Shangqian Gao +1

Text-to-image (T2I) diffusion models have demonstrated impressive image generation capabilities. Still, their computational intensity prohibits resource-constrained organizations f…