most citedHierarchical Self-Prompting SAM: A Prompt-Free Medical Image Segmentation Framework

1 citations · 2 across the 4 of their papers we have counts for

collaborators

8 papers

cs.RO20251 cited

Talk Less, Fly Lighter: Autonomous Semantic Compression for UAV Swarm Communication via LLMs

Fei Lin, Tengchao Zhang, Qinghua Ni +5

The rapid adoption of Large Language Models (LLMs) in unmanned systems has significantly enhanced the semantic understanding and autonomous task execution capabilities of Unmanned…

cs.CV20251 cited

Hierarchical Self-Prompting SAM: A Prompt-Free Medical Image Segmentation Framework

Mengmeng Zhang, Xingyuan Dai, Yicheng Sun +6

Although the Segment Anything Model (SAM) is highly effective in natural image segmentation, it requires dependencies on prompts, which limits its applicability to medical imaging…

cs.LG2025

Context-Aware Probabilistic Modeling with LLM for Multimodal Time Series Forecasting

Yueyang Yao, Jiajun Li, Xingyuan Dai +4

Time series forecasting is important for applications spanning energy markets, climate analysis, and traffic management. However, existing methods struggle to effectively integrate…

cs.LG2025

Offline Reinforcement Learning with Discrete Diffusion Skills

RuiXi Qiao, Jie Cheng, Xingyuan Dai +2

Skills have been introduced to offline reinforcement learning (RL) as temporal abstractions to tackle complex, long-horizon tasks, promoting consistent behavior and enabling meanin…

cs.RO2025

UAVs Meet LLMs: Overviews and Perspectives Toward Agentic Low-Altitude Mobility

Yonglin Tian, Fei Lin, Yiduo Li +11

Low-altitude mobility, exemplified by unmanned aerial vehicles (UAVs), has introduced transformative advancements across various domains, like transportation, logistics, and agricu…

cs.CV2024

MiniDrive: More Efficient Vision-Language Models with Multi-Level 2D Features as Text Tokens for Autonomous Driving

Enming Zhang, Xingyuan Dai, Min Huang +2

Vision-language models (VLMs) serve as general-purpose end-to-end models in autonomous driving, performing subtasks such as prediction, planning, and perception through question-an…