activity
20242026
collaborators

6 papers

cs.LG2026

Reinforced Collaboration in Multi-Agent Flow Networks

Zheng Wang, Yuang Liu, Yangkai Ding

Multi-agent systems provide a powerful way to extend large language models (LLMs) by decomposing a complex task into specialized subtasks handled by different agents. However, thei…

cs.LG2026

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone

DatologyAI, :, Siddharth Joshi +32

Data curation has shifted the quality-compute frontier for language-model and contrastive image-text pretraining, but its role for vision-language models (VLMs) is far less establi…

cs.CV2025

TrajSV: A Trajectory-based Model for Sports Video Representations and Applications

Zheng Wang, Shihao Xu, Wei Shi

Sports analytics has received significant attention from both academia and industry in recent years. Despite the growing interest and efforts in this field, several issues remain u…

cs.AI2025

InstructRAG: Leveraging Retrieval-Augmented Generation on Instruction Graphs for LLM-Based Task Planning

Zheng Wang, Shu Xian Teo, Jun Jie Chew +1

Recent advancements in large language models (LLMs) have enabled their use as agents for planning complex tasks. Existing methods typically rely on a thought-action-observation (TA…

cs.CL2024

Crafting Personalized Agents through Retrieval-Augmented Generation on Editable Memory Graphs

Zheng Wang, Zhongyang Li, Zeren Jiang +2

In the age of mobile internet, user data, often referred to as memories, is continuously generated on personal devices. Effectively managing and utilizing this data to deliver serv…

cs.CL2024

M-RAG: Reinforcing Large Language Model Performance through Retrieval-Augmented Generation with Multiple Partitions

Zheng Wang, Shu Xian Teo, Jieer Ouyang +2

Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by retrieving relevant memories from an external database. However, existing RAG methods typically organi…