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Zirui Li

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Open access Oct 2026

Physiological responses of the female sea urchins Heliocidaris crassispina to sub-chronic bisphenol C exposure.

Findings indicate that BPC exposure was associated with changes in gonadal morphology, lipid-positive area, redox-related biomarkers, and molecular profiles, although functional links and reproductive outcomes remain to be tested.

Qing-Song Shu, Qi-Yang Sun, De-Jian Su et al. · 0 citations
Preprint Sep 2026

SOR-Nav: Search or Relocate? Context-Gated Exploration and Cross-Region Relocation for Object Navigation

Object navigation requires an embodied agent to find an object in an unseen environment under partial observability and a limited motion budget. Existing methods primarily optimize where the robot should go next by ranking candidate destinations. In contrast to these methods, we present SOR-Nav, a hierarchical navigati...

Yuan Ji, Zi-Rui Li, Yu-Xin Cai et al. · 0 citations
#machine learning Preprint Sep 2026

Learning from Mixed-Quality Deployment Experience for Robot Manipulation

Predictive Action Chunk Learning first learns a predictive chunk-level critic that evaluates temporally extended action sequences and augments temporal difference learning with future latent prediction, providing richer supervision for long-horizon value estimation.

Yan-Gang Ren, Yu-Jie Yan, Zi-Rui Li et al. · 0 citations
#artificial intelligence Preprint Sep 2026

SSP-DMGTimeNet: Physics-Constrained Learning for Spatiotemporal Trajectory Prediction of Vehicle Platoons

SSP-DMGTimeNet, a physics-constrained learning framework for spatiotemporal trajectory prediction of vehicle platoons, combines multi-scale temporal representations with cross-vehicle interaction features to capture complex and time-varying platoon dynamics.

Yu-Hang Wang, Kai-Lang Ma, Zi-Rui Li et al. · 0 citations
Jul 2026

Ego-Dynamics-Augmented World Model for Autonomous Driving with Zero-Shot Cross-Chassis Adaptation

DynaDreamer is proposed, a dynamics-augmented Dreamer-style reinforcement learning method to address the problem of egocentric driving by augmenting the WM with an explicit ego-dynamics prior, and improves task success rates over the strongest baseline.

Zhidong Wang, Jingsong Liang, Zirui Li et al. · 0 citations

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