8 papers
FSVL: Taxonomic Fast-Slow Vision-to-Language Collaborative Framework for Interpretable Confusable Fish Species Identification and Knowledge Generation in the Middle Yangtze River
Meng Liang, Fucheng Wang, Lang Zhao +8
The Yangtze River Basin is a critical region for freshwater biodiversity conservation. The implementation of the Yangtze River Ten-Year Fishing Ban has increased the importance of…
Proactive Robot Assistance via Event-Driven Reasoning over State Changes
Fengkai Liu, Hao Su, Haozhuang Chi +6
Assistance in collaborative manipulation is often initiated by user instructions, making high-level reasoning request-driven. In fluent human teamwork, however, partners often infe…
THPL: A Vision-to-Language Decision Support Framework for Rainbow Trout Feeding Management in RAS
Meng Liang, Guanbo Feng, Haozhuang Chi +7
In Recirculating Aquaculture Systems (RAS), precision feeding is critical for minimizing costs and improving fish welfare. However, existing methods lack cognitive alignment betwee…
MomWorld: Momentum-Aware Latent World Model for Long-Horizon Autonomous Driving
Ziying Song, Shengkai Zhang, Lei Yang +6
Long-horizon planning enables autonomous vehicles to anticipate scene evolution and potential risks, supporting safe and stable decisions in complex interactions. However, existing…
PV-WM: A Heterogeneous Micro-Macro World Model for Articulated Pedestrian-Vehicle Co-Rollout
Haozhuang Chi, Jingsong Liang, Ziying Song +4
Local pedestrian-vehicle forecasting spans heterogeneous physical scales: pedestrians combine root locomotion with articulated motion, whereas vehicles are rigid bodies described b…
Driver-WM: A Driver-Centric Traffic-Conditioned Latent World Model for In-Cabin Dynamics Rollout
Haozhuang Chi, Daosheng Qiu, Hao Su +4
Safe L2/L3 driving automation requires anticipating human-in-the-loop reactions during shared-control transitions. While most driving world models forecast the external environment…
Risk-Aware Selective Multimodal Driver Monitoring with Driver-State World Modeling
Daosheng Qiu, Haozhuang Chi, Hao Su +4
Continuous driver monitoring in automated vehicles requires low-latency inference while avoiding unsafe decisions under uncertain driver states. Large vision-language models provid…
Event-Driven Proactive Assistive Manipulation with Grounded Vision-Language Planning
Fengkai Liu, Hao Su, Haozhuang Chi +6
Assistance in collaborative manipulation is often initiated by user instructions, making high-level reasoning request-driven. In fluent human teamwork, however, partners often infe…