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20172024
most citedEdit Everything: A Text-Guided Generative System for Images Editing

7 citations · 21 across the 16 of their papers we have counts for

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cs.CV20241 cited

Detecting, Explaining, and Mitigating Memorization in Diffusion Models

Yuxin Wen, Yuchen Liu, Chen Chen +1

Recent breakthroughs in diffusion models have exhibited exceptional image-generation capabilities. However, studies show that some outputs are merely replications of training data.…

cs.CL20241 cited

Robust Zero-Shot Text-to-Speech Synthesis with Reverse Inference Optimization

Yuchen Hu, Chen Chen, Siyin Wang +2

In this paper, we propose reverse inference optimization (RIO), a simple and effective method designed to enhance the robustness of autoregressive-model-based zero-shot text-to-spe…

cs.SD20241 cited

Zero-Shot Fake Video Detection by Audio-Visual Consistency

Xiaolou Li, Zehua Liu, Chen Chen +3

Recent studies have advocated the detection of fake videos as a one-class detection task, predicated on the hypothesis that the consistency between audio and visual modalities of g…

cs.CV2024

Ferret-v2: An Improved Baseline for Referring and Grounding with Large Language Models

Haotian Zhang, Haoxuan You, Philipp Dufter +8

While Ferret seamlessly integrates regional understanding into the Large Language Model (LLM) to facilitate its referring and grounding capability, it poses certain limitations: co…

cs.CV2024

Towards Memorization-Free Diffusion Models

Chen Chen, Daochang Liu, Chang Xu

Pretrained diffusion models and their outputs are widely accessible due to their exceptional capacity for synthesizing high-quality images and their open-source nature. The users,…

cs.CL20241 cited

InsCL: A Data-efficient Continual Learning Paradigm for Fine-tuning Large Language Models with Instructions

Yifan Wang, Yafei Liu, Chufan Shi +4

Instruction tuning effectively optimizes Large Language Models (LLMs) for downstream tasks. Due to the changing environment in real-life applications, LLMs necessitate continual ta…