10 citations · 24 across the 11 of their papers we have counts for
13 papers
ScIRGen: Synthesize Realistic and Large-Scale RAG Dataset for Scientific Research
Junyong Lin, Lu Dai, Ruiqian Han +7
Scientific researchers need intensive information about datasets to effectively evaluate and develop theories and methodologies. The information needs regarding datasets are implic…
TP-RAG: Benchmarking Retrieval-Augmented Large Language Model Agents for Spatiotemporal-Aware Travel Planning
Hang Ni, Fan Liu, Xinyu Ma +5
Large language models (LLMs) have shown promise in automating travel planning, yet they often fall short in addressing nuanced spatiotemporal rationality. While existing benchmarks…
SePer: Measure Retrieval Utility Through The Lens Of Semantic Perplexity Reduction
Lu Dai, Yijie Xu, Jinhui Ye +2
Large Language Models (LLMs) have demonstrated improved generation performance by incorporating externally retrieved knowledge, a process known as retrieval-augmented generation (R…
Improve Dense Passage Retrieval with Entailment Tuning
Lu Dai, Hao Liu, Hui Xiong
Retrieval module can be plugged into many downstream NLP tasks to improve their performance, such as open-domain question answering and retrieval-augmented generation. The key to a…
Labor Migration Modeling through Large-scale Job Query Data
Zhuoning Guo, Le Zhang, Hengshu Zhu +3
Accurate and timely modeling of labor migration is crucial for various urban governance and commercial tasks, such as local policy-making and business site selection. However, exis…
Meta-Transfer Learning Powered Temporal Graph Networks for Cross-City Real Estate Appraisal
Weijia Zhang, Jindong Han, Hao Liu +3
Real estate appraisal is important for a variety of endeavors such as real estate deals, investment analysis, and real property taxation. Recently, deep learning has shown great pr…
Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series
Weijia Zhang, Chenlong Yin, Hao Liu +1
Pre-trained Language Models (PLMs), such as ChatGPT, have significantly advanced the field of natural language processing. This progress has inspired a series of innovative studies…
Interpretable Cascading Mixture-of-Experts for Urban Traffic Congestion Prediction
Wenzhao Jiang, Jindong Han, Hao Liu +3
Rapid urbanization has significantly escalated traffic congestion, underscoring the need for advanced congestion prediction services to bolster intelligent transportation systems.…
Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models
Weijia Zhang, Jindong Han, Zhao Xu +4
The integration of machine learning techniques has become a cornerstone in the development of intelligent urban services, significantly contributing to the enhancement of urban eff…
LLMLight: Large Language Models as Traffic Signal Control Agents
Siqi Lai, Zhao Xu, Weijia Zhang +2
Traffic Signal Control (TSC) is a crucial component in urban traffic management, aiming to optimize road network efficiency and reduce congestion. Traditional TSC methods, primaril…
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook
Wenzhao Jiang, Hao Liu, Hui Xiong
Graph Neural Networks (GNNs) have emerged as powerful representation learning tools for capturing complex dependencies within diverse graph-structured data. Despite their success i…
Machine Learning for Urban Air Quality Analytics: A Survey
Jindong Han, Weijia Zhang, Hao Liu +1
The increasing air pollution poses an urgent global concern with far-reaching consequences, such as premature mortality and reduced crop yield, which significantly impact various a…
Cloth2Body: Generating 3D Human Body Mesh from 2D Clothing
Lu Dai, Liqian Ma, Shenhan Qian +3
In this paper, we define and study a new Cloth2Body problem which has a goal of generating 3D human body meshes from a 2D clothing image. Unlike the existing human mesh recovery pr…