Internlm-xcomposer-2.5: A versatile large vision language model supporting long-contextual input and output
We present InternLM-XComposer-2.5 (IXC-2.5), a versatile large-vision language model that
supports long-contextual input and output. IXC-2.5 excels in various text-image …
supports long-contextual input and output. IXC-2.5 excels in various text-image …
Mme-survey: A comprehensive survey on evaluation of multimodal llms
As a prominent direction of Artificial General Intelligence (AGI), Multimodal Large Language
Models (MLLMs) have garnered increased attention from both industry and academia …
Models (MLLMs) have garnered increased attention from both industry and academia …
Vlmevalkit: An open-source toolkit for evaluating large multi-modality models
We present VLMEvalKit: an open-source toolkit for evaluating large multi-modality models
based on PyTorch. The toolkit aims to provide a user-friendly and comprehensive framework …
based on PyTorch. The toolkit aims to provide a user-friendly and comprehensive framework …
Kangaroo: A powerful video-language model supporting long-context video input
Rapid advancements have been made in extending Large Language Models (LLMs) to
Large Multi-modal Models (LMMs). However, extending input modality of LLMs to video data …
Large Multi-modal Models (LMMs). However, extending input modality of LLMs to video data …
Oryx mllm: On-demand spatial-temporal understanding at arbitrary resolution
Visual data comes in various forms, ranging from small icons of just a few pixels to long
videos spanning hours. Existing multi-modal LLMs usually standardize these diverse visual …
videos spanning hours. Existing multi-modal LLMs usually standardize these diverse visual …
A survey on evaluation of multimodal large language models
J Huang, J Zhang - arXiv preprint arXiv:2408.15769, 2024 - arxiv.org
Multimodal Large Language Models (MLLMs) mimic human perception and reasoning
system by integrating powerful Large Language Models (LLMs) with various modality …
system by integrating powerful Large Language Models (LLMs) with various modality …
Expanding performance boundaries of open-source multimodal models with model, data, and test-time scaling
We introduce InternVL 2.5, an advanced multimodal large language model (MLLM) series
that builds upon InternVL 2.0, maintaining its core model architecture while introducing …
that builds upon InternVL 2.0, maintaining its core model architecture while introducing …
AMEGO: Active Memory from long EGOcentric videos
Egocentric videos provide a unique perspective into individuals' daily experiences, yet their
unstructured nature presents challenges for perception. In this paper, we introduce AMEGO …
unstructured nature presents challenges for perception. In this paper, we introduce AMEGO …
Points: Improving your vision-language model with affordable strategies
In recent years, vision-language models have made significant strides, excelling in tasks like
optical character recognition and geometric problem-solving. However, several critical …
optical character recognition and geometric problem-solving. However, several critical …
Timemarker: A versatile video-llm for long and short video understanding with superior temporal localization ability
Rapid development of large language models (LLMs) has significantly advanced multimodal
large language models (LMMs), particularly in vision-language tasks. However, existing …
large language models (LMMs), particularly in vision-language tasks. However, existing …