11 papers
InfinityEdit: Infinite Video Editing with a Lightweight Edit-Ignition Adapter
Yunze Tong, Mushui Liu, Canyu Zhao +9
With large pretrained models, existing methods have effectively improved instruction-based video editing. However, most of them rely on an in-place editing assumption. They align t…
LLaVA-OneVision-2: Towards Next-Generation Perceptual Intelligence
Xiang An, Yin Xie, Feilong Tang +27
We introduce LLaVA-OneVision-2 (LLaVA-OV-2), the most capable vision-language model in the LLaVA-OneVision series to date, achieving superior performance across a broad range of mu…
Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices
Tao Shen, Didi Zhu, Ziyu Zhao +3
The remarkable success of foundation models has been driven by scaling laws, demonstrating that model performance improves predictably with increased training data and model size.…
Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging
Jinluan Yang, Dingnan Jin, Anke Tang +10
Achieving balanced alignment of large language models (LLMs) in terms of Helpfulness, Honesty, and Harmlessness (3H optimization) constitutes a cornerstone of responsible AI. Exist…
Watch Wider and Think Deeper: Collaborative Cross-modal Chain-of-Thought for Complex Visual Reasoning
Wenting Lu, Didi Zhu, Tao Shen +3
Multi-modal reasoning requires the seamless integration of visual and linguistic cues, yet existing Chain-of-Thought methods suffer from two critical limitations in cross-modal sce…
OmniEduBench: A Comprehensive Chinese Benchmark for Evaluating Large Language Models in Education
Min Zhang, Hao Chen, Wenqi Zhang +6
With the rapid development of large language models (LLMs), various LLM-based works have been widely applied in educational fields. However, most existing LLMs and their benchmarks…