Mm-llms: Recent advances in multimodal large language models

D Zhang, Y Yu, J Dong, C Li, D Su, C Chu… - arxiv preprint arxiv …, 2024 - arxiv.org
In the past year, MultiModal Large Language Models (MM-LLMs) have undergone
substantial advancements, augmenting off-the-shelf LLMs to support MM inputs or outputs …

A systematic survey and critical review on evaluating large language models: Challenges, limitations, and recommendations

MTR Laskar, S Alqahtani, MS Bari… - Proceedings of the …, 2024 - aclanthology.org
Abstract Large Language Models (LLMs) have recently gained significant attention due to
their remarkable capabilities in performing diverse tasks across various domains. However …

The llama 3 herd of models

A Dubey, A Jauhri, A Pandey, A Kadian… - arxiv preprint arxiv …, 2024 - arxiv.org
Modern artificial intelligence (AI) systems are powered by foundation models. This paper
presents a new set of foundation models, called Llama 3. It is a herd of language models …

[PDF][PDF] Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond

J Bai, S Bai, S Yang, S Wang… - arxiv preprint …, 2023 - storage.prod.researchhub.com
In this work, we introduce the Qwen-VL series, a set of large-scale vision-language models
(LVLMs) designed to perceive and understand both texts and images. Starting from the …

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

G Team, P Georgiev, VI Lei, R Burnell, L Bai… - arxiv preprint arxiv …, 2024 - arxiv.org
In this report, we introduce the Gemini 1.5 family of models, representing the next generation
of highly compute-efficient multimodal models capable of recalling and reasoning over fine …

Llama-adapter: Efficient fine-tuning of language models with zero-init attention

R Zhang, J Han, C Liu, P Gao, A Zhou, X Hu… - arxiv preprint arxiv …, 2023 - arxiv.org
We present LLaMA-Adapter, a lightweight adaption method to efficiently fine-tune LLaMA
into an instruction-following model. Using 52K self-instruct demonstrations, LLaMA-Adapter …

How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites

Z Chen, W Wang, H Tian, S Ye, Z Gao, E Cui… - Science China …, 2024 - Springer
In this paper, we introduce InternVL 1.5, an open-source multimodal large language model
(MLLM) to bridge the capability gap between open-source and proprietary commercial …

Qwen-vl: A frontier large vision-language model with versatile abilities

J Bai, S Bai, S Yang, S Wang, S Tan, P Wang… - arxiv preprint arxiv …, 2023 - arxiv.org
In this work, we introduce the Qwen-VL series, a set of large-scale vision-language models
(LVLMs) designed to perceive and understand both texts and images. Starting from the …

MM1: methods, analysis and insights from multimodal LLM pre-training

B McKinzie, Z Gan, JP Fauconnier, S Dodge… - … on Computer Vision, 2024 - Springer
In this work, we discuss building performant Multimodal Large Language Models (MLLMs).
In particular, we study the importance of various architecture components and data choices …

Llama-adapter v2: Parameter-efficient visual instruction model

P Gao, J Han, R Zhang, Z Lin, S Geng, A Zhou… - arxiv preprint arxiv …, 2023 - arxiv.org
How to efficiently transform large language models (LLMs) into instruction followers is
recently a popular research direction, while training LLM for multi-modal reasoning remains …