114 citations · 140 across the 6 of their papers we have counts for
6 papers
ChatCoder: Chat-based Refine Requirement Improves LLMs' Code Generation
Zejun Wang, Jia Li, Ge Li +1
Large language models have shown good performances in generating code to meet human requirements. However, human requirements expressed in natural languages can be vague, incomplet…
Bridge the Gap between Language models and Tabular Understanding
Nuo Chen, Linjun Shou, Ming Gong +5
Table pretrain-then-finetune paradigm has been proposed and employed at a rapid pace after the success of pre-training in the natural language domain. Despite the promising finding…
ALBench: A Framework for Evaluating Active Learning in Object Detection
Zhanpeng Feng, Shiliang Zhang, Rinyoichi Takezoe +5
Active learning is an important technology for automated machine learning systems. In contrast to Neural Architecture Search (NAS) which aims at automating neural network architect…
Multi-view Face Detection Using Deep Convolutional Neural Networks
Sachin Sudhakar Farfade, Mohammad Saberian, Li-Jia Li
In this paper we consider the problem of multi-view face detection. While there has been significant research on this problem, current state-of-the-art approaches for this task req…
Visual Sentiment Prediction with Deep Convolutional Neural Networks
Can Xu, Suleyman Cetintas, Kuang-Chih Lee +1
Images have become one of the most popular types of media through which users convey their emotions within online social networks. Although vast amount of research is devoted to se…
Large-Scale Multi-Label Learning with Incomplete Label Assignments
Xiangnan Kong, Zhaoming Wu, Li-Jia Li +4
Multi-label learning deals with the classification problems where each instance can be assigned with multiple labels simultaneously. Conventional multi-label learning approaches ma…