75 citations · 77 across the 8 of their papers we have counts for
8 papers
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…
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…
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…
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…
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…
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…
SC-Tune: Unleashing Self-Consistent Referential Comprehension in Large Vision Language Models
Tongtian Yue, Jie Cheng, Longteng Guo +6
Recent trends in Large Vision Language Models (LVLMs) research have been increasingly focusing on advancing beyond general image understanding towards more nuanced, object-level re…
RIME: Robust Preference-based Reinforcement Learning with Noisy Preferences
Jie Cheng, Gang Xiong, Xingyuan Dai +3
Preference-based Reinforcement Learning (PbRL) circumvents the need for reward engineering by harnessing human preferences as the reward signal. However, current PbRL methods exces…