Ferret-v2: An Advanced Multimodal Language Model for Improved Referring, Grounding, and Visual Understanding
Ferret-v2 is a significant upgrade to the Ferret model, featuring advanced capabilities in handling any resolution referring and grounding, multi-granularity visual encoding, and a novel three-stage training pipeline, enabling it to excel in processing and understanding images with higher resolution and finer detail.
Efficient Multimodal Large Language Model with Small Backbones: Introducing TinyGPT-V
TinyGPT-V is a novel open-source multimodal large language model designed for efficient training and inference across various vision-language tasks, leveraging a compact yet powerful architecture that integrates the Phi-2 language model with pre-trained vision encoders.
Mitigating Multimodal Hallucination in Large Language Models through Self-Feedback Guided Revision
VOLCANO, a multimodal self-feedback guided revision model, effectively reduces multimodal hallucination and achieves state-of-the-art performance on multimodal hallucination benchmarks.
AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling
AnyGPTは、異なるモダリティ（音声、テキスト、画像、音楽）を統合的に処理するために離散表現を利用する多対多の言語モデルであり、既存のLLMアーキテクチャやトレーニング手法を変更せずに安定して訓練できることを示しています。
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