activity
20242026
most citedMulti-task Offline Reinforcement Learning for Online Advertising in Recommender Systems

4 citations · 11 across the 14 of their papers we have counts for

collaborators

14 papers

cs.AI2026

InsTraj: Instructing Diffusion Models with Travel Intentions to Generate Real-world Trajectories

Yuanshao Zhu, Yuxuan Liang, Xiangyu Zhao +5

The generation of realistic and controllable GPS trajectories is a fundamental task for applications in urban planning, mobility simulation, and privacy-preserving data sharing. Ho…

cs.CV2025

Renormalization Group Guided Tensor Network Structure Search

Maolin Wang, Bowen Yu, Sheng Zhang +8

Tensor network structure search (TN-SS) aims to automatically discover optimal network topologies and rank configurations for efficient tensor decomposition in high-dimensional dat…

cs.CL2025

MTA: A Merge-then-Adapt Framework for Personalized Large Language Model

Xiaopeng Li, Yuanjin Zheng, Wanyu Wang +6

Personalized Large Language Models (PLLMs) aim to align model outputs with individual user preferences, a crucial capability for user-centric applications. However, the prevalent a…

cs.AI2025

Boosting Fine-Grained Urban Flow Inference via Lightweight Architecture and Focalized Optimization

Yuanshao Zhu, Xiangyu Zhao, Zijian Zhang +2

Fine-grained urban flow inference is crucial for urban planning and intelligent transportation systems, enabling precise traffic management and resource allocation. However, the pr…

cs.LG2025

DANCE: Resource-Efficient Neural Architecture Search with Data-Aware and Continuous Adaptation

Maolin Wang, Tianshuo Wei, Sheng Zhang +6

Neural Architecture Search (NAS) has emerged as a powerful approach for automating neural network design. However, existing NAS methods face critical limitations in real-world depl…

cs.IR2025★ 4 cited

Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems

Langming Liu, Wanyu Wang, Chi Zhang +6

Online advertising in recommendation platforms has gained significant attention, with a predominant focus on channel recommendation and budget allocation strategies. However, curre…

cs.CV2025

Learning Generalized and Flexible Trajectory Models from Omni-Semantic Supervision

Yuanshao Zhu, James Jianqiao Yu, Xiangyu Zhao +4

The widespread adoption of mobile devices and data collection technologies has led to an exponential increase in trajectory data, presenting significant challenges in spatio-tempor…

cs.IR2025

STAR-Rec: Making Peace with Length Variance and Pattern Diversity in Sequential Recommendation

Maolin Wang, Sheng Zhang, Ruocheng Guo +6

Recent deep sequential recommendation models often struggle to effectively model key characteristics of user behaviors, particularly in handling sequence length variations and capt…

cs.CL2025★ 1 cited

Sliding Window Attention Training for Efficient Large Language Models

Zichuan Fu, Wentao Song, Yejing Wang +7

Recent advances in transformer-based Large Language Models (LLMs) have demonstrated remarkable capabilities across various tasks. However, their quadratic computational complexity…

cs.ET2024★ 2 cited

UniTraj: Learning a Universal Trajectory Foundation Model from Billion-Scale Worldwide Traces

Yuanshao Zhu, James Jianqiao Yu, Xiangyu Zhao +4

Building a universal trajectory foundation model is a promising solution to address the limitations of existing trajectory modeling approaches, such as task specificity, regional d…

cs.IR2024★ 1 cited

GPRec: Bi-level User Modeling for Deep Recommenders

Yejing Wang, Dong Xu, Xiangyu Zhao +7

GPRec explicitly categorizes users into groups in a learnable manner and aligns them with corresponding group embeddings. We design the dual group embedding space to offer a divers…

cs.LG2024

GARLIC: GPT-Augmented Reinforcement Learning with Intelligent Control for Vehicle Dispatching

Xiao Han, Zijian Zhang, Xiangyu Zhao +6

As urban residents demand higher travel quality, vehicle dispatch has become a critical component of online ride-hailing services. However, current vehicle dispatch systems struggl…

cs.CV2024★ 2 cited

G3: An Effective and Adaptive Framework for Worldwide Geolocalization Using Large Multi-Modality Models

Pengyue Jia, Yiding Liu, Xiaopeng Li +7

Worldwide geolocalization aims to locate the precise location at the coordinate level of photos taken anywhere on the Earth. It is very challenging due to 1) the difficulty of capt…

cs.LG2024★ 1 cited

ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model

Yuanshao Zhu, James Jianqiao Yu, Xiangyu Zhao +6

Generating trajectory data is among promising solutions to addressing privacy concerns, collection costs, and proprietary restrictions usually associated with human mobility analys…