1 citations · 2 across the 12 of their papers we have counts for
4 papers · 1 filter
PANTHER: Generative Pretraining Beyond Language for Sequential User Behavior Modeling
Guilin Li, Yun Zhang, Xiuyuan Chen +6
Large language models (LLMs) have shown that generative pretraining can distill vast world knowledge into compact token representations. While LLMs encapsulate extensive world know…
Urban In-Context Learning: Bridging Pretraining and Inference through Masked Diffusion for Urban Profiling
Ruixing Zhang, Bo Wang, Tongyu Zhu +2
Urban profiling aims to predict urban profiles in unknown regions and plays a critical role in economic and social censuses. Existing approaches typically follow a two-stage paradi…
MindSpeed RL: Distributed Dataflow for Scalable and Efficient RL Training on Ascend NPU Cluster
Laingjun Feng, Chenyi Pan, Xinjie Guo +11
Reinforcement learning (RL) is a paradigm increasingly used to align large language models. Popular RL algorithms utilize multiple workers and can be modeled as a graph, where each…
Generative Pretraining at Scale: Transformer-Based Encoding of Transactional Behavior for Fraud Detection
Ze Yu Zhao, Zheng Zhu, Guilin Li +2
In this work, we introduce an innovative autoregressive model leveraging Generative Pretrained Transformer (GPT) architectures, tailored for fraud detection in payment systems. Our…