S3: A Simple Strong Sample-effective Multimodal Dialog System

• URL: http://arxiv.org/abs/2406.18305v1
• Date: Wed, 26 Jun 2024 12:45:43 GMT
• Title: S3: A Simple Strong Sample-effective Multimodal Dialog System
• Authors: Elisei Rykov, Egor Malkershin, Alexander Panchenko,
• Abstract summary: We present a conceptually simple yet powerful baseline for the multimodal dialog task, an S3 model, that achieves near state-of-the-art results. The system is based on a pre-trained large language model, pre-trained modality encoders for image and audio, and a trainable modality projector.
• Score: 61.31055673156622
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this work, we present a conceptually simple yet powerful baseline for the multimodal dialog task, an S3 model, that achieves near state-of-the-art results on two compelling leaderboards: MMMU and AI Journey Contest 2023. The system is based on a pre-trained large language model, pre-trained modality encoders for image and audio, and a trainable modality projector. The proposed effective data mixture for training such an architecture demonstrates that a multimodal model based on a strong language model and trained on a small amount of multimodal data can perform efficiently in the task of multimodal dialog.

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