134 citations · 249 across the 8 of their papers we have counts for
8 papers
TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems
Yilun Kong, Jingqing Ruan, Yihong Chen +9
Large Language Models (LLMs) have demonstrated proficiency in addressing tasks that necessitate a combination of task planning and the usage of external tools that require a blend…
SeqCo-DETR: Sequence Consistency Training for Self-Supervised Object Detection with Transformers
Guoqiang Jin, Fan Yang, Mingshan Sun +7
Self-supervised pre-training and transformer-based networks have significantly improved the performance of object detection. However, most of the current self-supervised object det…
Explore the Power of Synthetic Data on Few-shot Object Detection
Shaobo Lin, Kun Wang, Xingyu Zeng +1
Few-shot object detection (FSOD) aims to expand an object detector for novel categories given only a few instances for training. The few training samples restrict the performance o…
An Effective Crop-Paste Pipeline for Few-shot Object Detection
Shaobo Lin, Kun Wang, Xingyu Zeng +1
Few-shot object detection (FSOD) aims to expand an object detector for novel categories given only a few instances for training. However, detecting novel categories with only a few…
Explore the Power of Dropout on Few-shot Learning
Shaobo Lin, Xingyu Zeng, Rui Zhao
The generalization power of the pre-trained model is the key for few-shot deep learning. Dropout is a regularization technique used in traditional deep learning methods. In this pa…
Crafting GBD-Net for Object Detection
Xingyu Zeng, Wanli Ouyang, Junjie Yan +9
The visual cues from multiple support regions of different sizes and resolutions are complementary in classifying a candidate box in object detection. Effective integration of loca…