A Survey of Multimodel Large Language Models

Z Liang, Y Xu, Y Hong, P Shang, Q Wang… - Proceedings of the 3rd …, 2024 - dl.acm.org
With the widespread application of the Transformer architecture in various modalities,
including vision, the technology of large language models is evolving from a single modality …

A survey on hallucination in large vision-language models

H Liu, W Xue, Y Chen, D Chen, X Zhao, K Wang… - arxiv preprint arxiv …, 2024 - arxiv.org
Recent development of Large Vision-Language Models (LVLMs) has attracted growing
attention within the AI landscape for its practical implementation potential. However,`` …

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 …

Video-llava: Learning united visual representation by alignment before projection

B Lin, Y Ye, B Zhu, J Cui, M Ning, P **… - arxiv preprint arxiv …, 2023 - arxiv.org
The Large Vision-Language Model (LVLM) has enhanced the performance of various
downstream tasks in visual-language understanding. Most existing approaches encode …

Unified-io 2: Scaling autoregressive multimodal models with vision language audio and action

J Lu, C Clark, S Lee, Z Zhang… - Proceedings of the …, 2024 - openaccess.thecvf.com
We present Unified-IO 2 a multimodal and multi-skill unified model capable of following
novel instructions. Unified-IO 2 can use text images audio and/or videos as input and can …

Mathverse: Does your multi-modal llm truly see the diagrams in visual math problems?

R Zhang, D Jiang, Y Zhang, H Lin, Z Guo, P Qiu… - … on Computer Vision, 2024 - Springer
The remarkable progress of Multi-modal Large Language Models (MLLMs) has gained
unparalleled attention. However, their capabilities in visual math problem-solving remain …

Onellm: One framework to align all modalities with language

J Han, K Gong, Y Zhang, J Wang… - Proceedings of the …, 2024 - openaccess.thecvf.com
Multimodal large language models (MLLMs) have gained significant attention due to their
strong multimodal understanding capability. However existing works rely heavily on modality …

Pointllm: Empowering large language models to understand point clouds

R Xu, X Wang, T Wang, Y Chen, J Pang… - European Conference on …, 2024 - Springer
The unprecedented advancements in Large Language Models (LLMs) have shown a
profound impact on natural language processing but are yet to fully embrace the realm of 3D …

Llava-next-interleave: Tackling multi-image, video, and 3d in large multimodal models

F Li, R Zhang, H Zhang, Y Zhang, B Li, W Li… - arxiv preprint arxiv …, 2024 - arxiv.org
Visual instruction tuning has made considerable strides in enhancing the capabilities of
Large Multimodal Models (LMMs). However, existing open LMMs largely focus on single …

Hallucination of multimodal large language models: A survey

Z Bai, P Wang, T **ao, T He, Z Han, Z Zhang… - arxiv preprint arxiv …, 2024 - arxiv.org
This survey presents a comprehensive analysis of the phenomenon of hallucination in
multimodal large language models (MLLMs), also known as Large Vision-Language Models …