5 citations · 6 across the 3 of their papers we have counts for
9 papers
Temporal Tokenization Strategies for Event Sequence Modeling with Large Language Models
Zefang Liu, Nam H. Nguyen, Yinzhu Quan +1
Representing continuous time is a critical and under-explored challenge in modeling temporal event sequences with large language models (LLMs). Various strategies like byte-level r…
CRMAgent: A Multi-Agent LLM System for E-Commerce CRM Message Template Generation
Yinzhu Quan, Xinrui Li, Ying Chen
In e-commerce private-domain channels such as instant messaging and e-mail, merchants engage customers directly as part of their Customer Relationship Management (CRM) programmes t…
EconWebArena: Benchmarking Autonomous Agents on Economic Tasks in Realistic Web Environments
Zefang Liu, Yinzhu Quan
We introduce EconWebArena, a benchmark for evaluating autonomous agents on complex, multimodal economic tasks in realistic web environments. The benchmark comprises 360 curated tas…
Leveraging Large Language Models for Risk Assessment in Hyperconnected Logistic Hub Network Deployment
Yinzhu Quan, Yujia Xu, Guanlin Chen +2
The growing emphasis on energy efficiency and environmental sustainability in global supply chains introduces new challenges in the deployment of hyperconnected logistic hub networ…
Retrieval of Temporal Event Sequences from Textual Descriptions
Zefang Liu, Yinzhu Quan
Retrieving temporal event sequences from textual descriptions is crucial for applications such as analyzing e-commerce behavior, monitoring social media activities, and tracking cr…
TPP-LLM: Modeling Temporal Point Processes by Efficiently Fine-Tuning Large Language Models
Zefang Liu, Yinzhu Quan
Temporal point processes (TPPs) are widely used to model the timing and occurrence of events in domains such as social networks, transportation systems, and e-commerce. In this pap…