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From Image to Video, what do we need in multimodal LLMs?
Multimodal Large Language Models (MLLMs) have demonstrated profound capabilities in understanding multimodal information, covering from Image LLMs to the more complex Video LLMs.
NoteLLM: A Retrievable Large Language Model for Note Recommendation
Indeed, learning to generate hashtags/categories can potentially enhance note embeddings, both of which compress key note information into limited content.
Single-Channel EEG Based Arousal Level Estimation Using Multitaper Spectrum Estimation at Low-Power Wearable Devices
This paper proposes a novel lightweight method using the multitaper power spectrum to estimate arousal levels at wearable devices.
A multi-branch convolutional neural network for detecting double JPEG compression
In this paper, we present a CNN solution by using raw DCT (discrete cosine transformation) coefficients from JPEG images as input.
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