16 citations · 109 across the 30 of their papers we have counts for
11 papers · 1 filter
Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
Zhe Chen, Weiyun Wang, Yue Cao +39
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 signif…
Mini-InternVL: A Flexible-Transfer Pocket Multimodal Model with 5% Parameters and 90% Performance
Zhangwei Gao, Zhe Chen, Erfei Cui +12
Multimodal large language models (MLLMs) have demonstrated impressive performance in vision-language tasks across a broad spectrum of domains. However, the large model scale and as…
Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization
Weiyun Wang, Zhe Chen, Wenhai Wang +8
Existing open-source multimodal large language models (MLLMs) generally follow a training process involving pre-training and supervised fine-tuning. However, these models suffer fr…
MMInstruct: A High-Quality Multi-Modal Instruction Tuning Dataset with Extensive Diversity
Yangzhou Liu, Yue Cao, Zhangwei Gao +9
Despite the effectiveness of vision-language supervised fine-tuning in enhancing the performance of Vision Large Language Models (VLLMs). However, existing visual instruction tunin…
ChemVLM: Exploring the Power of Multimodal Large Language Models in Chemistry Area
Junxian Li, Di Zhang, Xunzhi Wang +16
Large Language Models (LLMs) have achieved remarkable success and have been applied across various scientific fields, including chemistry. However, many chemical tasks require the…
OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text
Qingyun Li, Zhe Chen, Weiyun Wang +37
Image-text interleaved data, consisting of multiple images and texts arranged in a natural document format, aligns with the presentation paradigm of internet data and closely resem…
Needle In A Multimodal Haystack
Weiyun Wang, Shuibo Zhang, Yiming Ren +13
With the rapid advancement of multimodal large language models (MLLMs), their evaluation has become increasingly comprehensive. However, understanding long multimodal content, as a…
How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites
Zhe Chen, Weiyun Wang, Hao Tian +32
In this report, we introduce InternVL 1.5, an open-source multimodal large language model (MLLM) to bridge the capability gap between open-source and proprietary commercial models…
Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures
Yuchen Duan, Weiyun Wang, Zhe Chen +7
Transformers have revolutionized computer vision and natural language processing, but their high computational complexity limits their application in high-resolution image processi…
The All-Seeing Project V2: Towards General Relation Comprehension of the Open World
Weiyun Wang, Yiming Ren, Haowen Luo +9
We present the All-Seeing Project V2: a new model and dataset designed for understanding object relations in images. Specifically, we propose the All-Seeing Model V2 (ASMv2) that i…
MM-Interleaved: Interleaved Image-Text Generative Modeling via Multi-modal Feature Synchronizer
Changyao Tian, Xizhou Zhu, Yuwen Xiong +10
Developing generative models for interleaved image-text data has both research and practical value. It requires models to understand the interleaved sequences and subsequently gene…