🏢 Tongji University

LLM-powered Tri-level learning framework enhances time series OOD generalization.

RCDN: Robust, camera-insensitive collaborative perception via dynamic 3D neural modeling, overcoming camera failures for high-performance autonomous systems.

Improved unsupervised domain adaptation framework achieves superior performance via refined f-divergence and novel f-domain discrepancy, enabling faster algorithms and tighter generalization bounds.

NeuroClips: groundbreaking fMRI-to-video reconstruction, achieving high-fidelity smooth video up to 6s at 8FPS by decoding both high-level semantics and low-level perception flows.

MoTE: A novel framework harmonizes generalization and specialization for visual-language video knowledge transfer, achieving state-of-the-art results.

Hyper-opinion Evidential Deep Learning (HEDL) enhances out-of-distribution detection by integrating sharp and vague evidence for superior uncertainty estimation and classification accuracy.

GeoNLF: Geometry-guided Pose-free Neural LiDAR Fields revolutionizes LiDAR point cloud processing by cleverly combining neural and geometric optimization for superior novel view synthesis and multi-vi…

New information-theoretic generalization bounds, based on conditional f-information, improve existing methods by addressing unboundedness and offering a generic approach applicable to various loss fun…

GDeR: A novel dynamic graph pruning method boosts GNN training efficiency and robustness by intelligently selecting a representative subset of training data, mitigating issues caused by imbalanced or …

Zero-shot online action detection gets a boost! OV-OAD leverages vision-language models and text supervision to achieve impressive performance on various benchmarks without relying on manual annotati…

AlchemistCoder enhances code LLMs by pioneering hindsight tuning on multi-source data, harmonizing conflicting styles via AlchemistPrompts, and achieving state-of-the-art performance.