9 citations · 33 across the 24 of their papers we have counts for
14 papers · 1 filter
Coarse-to-Fine Multi-Resolution Diffusion Models for Trajectory Generation in Urban Systems
Wen Ye, Muyan Weng, Chuizheng Meng +3
Understanding human mobility is critical for a wide range of urban applications, including traffic management, epidemic control, and urban planning. However, due to privacy concern…
On the Implicit Reward Overfitting and the Low-rank Dynamics in RLVR
Hao Ye, Jisheng Dang, Junfeng Fang +7
Recent extensive research has demonstrated that the enhanced reasoning capabilities acquired by models through Reinforcement Learning with Verifiable Rewards (RLVR) are primarily c…
Training Generalizable Collaborative Agents via Strategic Risk Aversion
Chengrui Qu, Yizhou Zhang, Nicolas Lanzetti +1
Many emerging agentic paradigms require agents to collaborate with one another (or people) to achieve shared goals. Unfortunately, existing approaches to learning policies for such…
When Does Learning Renormalize? Sufficient Conditions for Power Law Spectral Dynamics
Yizhou Zhang
Empirical power--law scaling has been widely observed across modern deep learning systems, yet its theoretical origins and scope of validity remain incompletely understood. The Gen…
Renormalizable Spectral-Shell Dynamics as the Origin of Neural Scaling Laws
Yizhou Zhang
Neural scaling laws and double-descent phenomena suggest that deep-network training obeys a simple macroscopic structure despite highly nonlinear optimization dynamics. We derive s…
Data Curation Through the Lens of Spectral Dynamics: Static Limits, Dynamic Acceleration, and Practical Oracles
Yizhou Zhang, Lun Du
Large-scale neural models are increasingly trained with data pruning, synthetic data generation, cross-model distillation, reinforcement learning from human feedback (RLHF), and di…
A Generalized Spectral Framework to Expain Neural Scaling and Compression Dynamics
Yizhou Zhang
Empirical scaling laws describe how test loss and other performance metrics depend on model size, dataset size, and compute. While such laws are consistent within specific regimes,…
FastGRPO: Accelerating Policy Optimization via Concurrency-aware Speculative Decoding and Online Draft Learning
Yizhou Zhang, Ning Lv, Teng Wang +1
Group relative policy optimization (GRPO) has demonstrated significant potential in improving the reasoning capabilities of large language models (LLMs) via reinforcement learning.…
KL-regularization Itself is Differentially Private in Bandits and RLHF
Yizhou Zhang, Kishan Panaganti, Laixi Shi +2
Differential Privacy (DP) provides a rigorous framework for privacy, ensuring the outputs of data-driven algorithms remain statistically indistinguishable across datasets that diff…
TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis
Wen Ye, Wei Yang, Defu Cao +4
Time series analysis is crucial in real-world applications, yet traditional methods focus on isolated tasks only, and recent studies on time series reasoning remain limited to eith…
TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model
Defu Cao, Wen Ye, Yizhou Zhang +1
Foundation models, particularly Large Language Models (LLMs), have revolutionized text and video processing, yet time series data presents distinct challenges for such approaches d…
Global Convergence of Localized Policy Iteration in Networked Multi-Agent Reinforcement Learning
Yizhou Zhang, Guannan Qu, Pan Xu +3
We study a multi-agent reinforcement learning (MARL) problem where the agents interact over a given network. The goal of the agents is to cooperatively maximize the average of thei…
Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media
Yizhou Zhang, Defu Cao, Yan Liu
Recent years have witnessed the rise of misinformation campaigns that spread specific narratives on social media to manipulate public opinions on different areas, such as politics…
VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media
Yizhou Zhang, Karishma Sharma, Yan Liu
Recent years have witnessed an increasing use of coordinated accounts on social media, operated by misinformation campaigns to influence public opinion and manipulate social outcom…