5 papers
Benchmarking and Analyzing Generative Data for Visual Recognition
Bo Li, Haotian Liu, Liangyu Chen +3
Advancements in large pre-trained generative models have expanded their potential as effective data generators in visual recognition. This work delves into the impact of generative…
Otter: A Multi-Modal Model with In-Context Instruction Tuning
Bo Li, Yuanhan Zhang, Liangyu Chen +5
Recent advances in Large Multimodal Models (LMMs) have unveiled great potential as visual assistants. However, most existing works focus on responding to individual instructions or…
MMInA: Benchmarking Multihop Multimodal Internet Agents
Shulin Tian, Ziniu Zhang, Liangyu Chen +1
Autonomous embodied agents live on an Internet of multimedia websites. Can they hop around multimodal websites to complete complex user tasks? Existing benchmarks fail to assess th…
Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code
Taishi Nakamura, Mayank Mishra, Simone Tedeschi +42
Pretrained language models are an integral part of AI applications, but their high computational cost for training limits accessibility. Initiatives such as Bloom and StarCoder aim…
MMLongBench-Doc: Benchmarking Long-context Document Understanding with Visualizations
Yubo Ma, Yuhang Zang, Liangyu Chen +13
Understanding documents with rich layouts and multi-modal components is a long-standing and practical task. Recent Large Vision-Language Models (LVLMs) have made remarkable strides…