8 citations · 16 across the 7 of their papers we have counts for
7 papers
Slang Context-based Inference Enhancement via Greedy Search-Guided Chain-of-Thought Prompting
Jinghan Cao, Qingyang Ren, Xiangyun Chen +3
Slang interpretation has been a challenging downstream task for Large Language Models (LLMs) as the expressions are inherently embedded in contextual, cultural, and linguistic fram…
SVAC: Scaling Is All You Need For Referring Video Object Segmentation
Li Zhang, Haoxiang Gao, Zhihao Zhang +2
Referring Video Object Segmentation (RVOS) aims to segment target objects in video sequences based on natural language descriptions. While recent advances in Multi-modal Large Lang…
AdaptFlow: Adaptive Workflow Optimization via Meta-Learning
Runchuan Zhu, Bowen Jiang, Lingrui Mei +8
Recent advances in large language models (LLMs) have sparked growing interest in agentic workflows, which are structured sequences of LLM invocations intended to solve complex task…
Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving
Haoxiang Gao, Li Zhang, Yu Zhao +2
Vision-language models (VLMs) have become a promising approach to enhancing perception and decision-making in autonomous driving. The gap remains in applying VLMs to understand com…
Utilizing Large Language Models for Information Extraction from Real Estate Transactions
Yu Zhao, Haoxiang Gao, Jinghan Cao +1
Real estate sales contracts contain crucial information for property transactions, but manual data extraction can be time-consuming and error-prone. This paper explores the applica…
A Survey for Foundation Models in Autonomous Driving
Haoxiang Gao, Zhongruo Wang, Yaqian Li +3
The advent of foundation models has revolutionized the fields of natural language processing and computer vision, paving the way for their application in autonomous driving (AD). T…
Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention
Ming Zeng, Haoxiang Gao, Tong Yu +4
Deep neural networks, including recurrent networks, have been successfully applied to human activity recognition. Unfortunately, the final representation learned by recurrent netwo…