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20202026
most citedPersonalization of Large Language Models: A Survey

15 citations · 16 across the 24 of their papers we have counts for

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cs.CV2026

Joint and Cross-Modal Video-Audio Generation and Editing: A Unified Formulation and Design Taxonomy

Abhinav Sharma, Sai Karthik Navuluru, Wang Wei +21

Video and audio are perceived together, yet most generative models treat them in isolation. We examine methods that model the two modalities jointly, generate one from the other, o…

cs.CV2026

InfinityStory: Unlimited Video Generation with World Consistency and Character-Aware Shot Transitions

Mohamed Elmoghany, Liangbing Zhao, Xiaoqian Shen +27

Generating long-form storytelling videos with consistent visual narratives remains a significant challenge in video synthesis. We present a novel framework, dataset, and a model th…

cs.CV2026

Human-Aligned MLLM Judges for Fine-Grained Image Editing Evaluation: A Benchmark, Framework, and Analysis

Runzhou Liu, Hailey Weingord, Sejal Mittal +18

Evaluating image editing models remains challenging due to the coarse granularity and limited interpretability of traditional metrics, which often fail to capture aspects important…

cs.CV2025

A Survey on Long-Video Storytelling Generation: Architectures, Consistency, and Cinematic Quality

Mohamed Elmoghany, Ryan Rossi, Seunghyun Yoon +26

Despite the significant progress that has been made in video generative models, existing state-of-the-art methods can only produce videos lasting 5-16 seconds, often labeled "long-…

cs.CV2024

Personalized Multimodal Large Language Models: A Survey

Junda Wu, Hanjia Lyu, Yu Xia +24

Multimodal Large Language Models (MLLMs) have become increasingly important due to their state-of-the-art performance and ability to integrate multiple data modalities, such as tex…