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FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities
The rapid progress of large language models (LLMs) has catalyzed the emergence of multimodal large language models (MLLMs) that unify …
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FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities
INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling
Hallucinations in large vision-language models (LVLMs) pose significant challenges for real-world applications, as LVLMs may generate …
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INTER: Mitigating Hallucination in Large Vision-Language Models by Interaction Guidance Sampling
Forensics-Bench: A Comprehensive Forgery Detection Benchmark Suite for Large Vision Language Models
Recently, the rapid development of AIGC has significantly boosted the diversities of fake media spread in the Internet, posing …
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Forensics-Bench: A Comprehensive Forgery Detection Benchmark Suite for Large Vision Language Models
Megactor-sigma: Unlocking flexible mixed-modal control in portrait animation with diffusion transformer
Diffusion models have demonstrated superior performance in portrait animation. However, current approaches relied on either visual or …
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Megactor-sigma: Unlocking flexible mixed-modal control in portrait animation with diffusion transformer
MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models
The capability to process multiple images is crucial for Large Vision-Language Models (LVLMs) to develop a more thorough and nuanced …
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MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models
Sparse Beats Dense: Rethinking Supervision in Radar-Camera Depth Completion
It is widely believed that sparse supervision is worse than dense supervision in the field of depth completion, but the underlying …
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Sparse Beats Dense: Rethinking Supervision in Radar-Camera Depth Completion
Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic View
Compositional reasoning capabilities are usually considered as fundamental skills to characterize human perception. Recent studies show …
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Diagnosing the Compositional Knowledge of Vision Language Models from a Game-Theoretic View
MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI
Large Vision-Language Models (LVLMs) show significant strides in general-purpose multimodal applications such as visual dialogue and …
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MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI
Towards Understanding the Generalization of Deepfake Detectors from a Game-Theoretical View
This paper aims to explain the generalization of deepfake detectors from the novel perspective of multi-order interactions among visual …
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Towards Understanding the Generalization of Deepfake Detectors from a Game-Theoretical View
Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization
In this paper, we analyse the generalization ability of binary classifiers for the task of deepfake detection. We find that the …
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Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization