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20242026
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cs.LG2026

LLMSynthor: Macro-Aligned Micro-Records Synthesis with Large Language Models

Yihong Tang, Menglin Kong, Junlin He +3

Macro-aligned micro-records are crucial for credible simulations in social science and urban studies. For example, epidemic models are only reliable when individual-level mobility…

cs.LG2026

Bridge: Retrieval-Augmented Spatiotemporal Modeling for Urban Delivery Demand

Yihong Tang, Tong Nie, Junlin He +3

Forecasting urban delivery demand becomes substantially more challenging when newly added service regions lack historical records. Existing spatiotemporal forecasters effectively m…

cs.LG2026

ADV-0: Closed-Loop Min-Max Adversarial Training for Long-Tail Robustness in Autonomous Driving

Tong Nie, Yihong Tang, Junlin He +5

Deploying autonomous driving systems requires robustness against long-tail scenarios that are rare but safety-critical. While adversarial training offers a promising solution, exis…

cs.LG2025

Solving Oversmoothing in GNNs via Nonlocal Message Passing: Algebraic Smoothing and Depth Scalability

Weiqi Guan, Junlin He

The relationship between Layer Normalization (LN) placement and the oversmoothing phenomenon remains underexplored. We identify a critical dilemma: Pre-LN architectures avoid overs…

cs.LG2025

Joint Estimation and Prediction of City-wide Delivery Demand: A Large Language Model Empowered Graph-based Learning Approach

Tong Nie, Junlin He, Yuewen Mei +4

The proliferation of e-commerce and urbanization has significantly intensified delivery operations in urban areas, boosting the volume and complexity of delivery demand. Data-drive…

cs.LG2024

Preventing Dimensional Collapse in Self-Supervised Learning via Orthogonality Regularization

Junlin He, Jinxiao Du, Wei Ma

Self-supervised learning (SSL) has rapidly advanced in recent years, approaching the performance of its supervised counterparts through the extraction of representations from unlab…