6 citations · 27 across the 25 of their papers we have counts for
28 papers
To Explore The Strange New World Beyond Data Distribution: System Behavior, Causality Tax, and Non-causal Base Model
Xianzhi Zeng, Jiangneng Li, Gao Cong
We show that the causality of language models (LMs) may not be necessary nor optimal. This is the case when system behavior (denoted as ) is incorporated as a first-principle Ba…
ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair
Chiwang Luk, Matin Mohammad Najafi, Zhifeng Jia +6
Large language model agents can repair real repository issues, but they often spend large context budgets on whole-file reads, broad searches, and long terminal outputs where usefu…
Demonstrating TOFFEE: A Learned System for Synthesizing Data Agent Trajectories at Scale
Ziting Wang, Yin Li, Zuhao Yang +3
LLM-powered data agents are playing an increasingly important role in data-driven decision making. However, existing data agents struggle to generalize to unseen data environments…
LiteTopK: Exploiting the Curse of Dimensionality for a Fused Indexer-TopK Kernel in Long-Context Sparse Attention
Ziqi Yin, Jianyang Gao, Peiqi Yin +2
Indexer-TopK, the operation to compute the scores and select the top-k candidates, is widely used by sparse attention algorithms in large language models and vector retrieval in re…
Data Agents Under Attack: Vulnerabilities in LLM-Driven Analytical Systems
Kuncan Wang, Ziting Wang, Peizhuo Lv +4
Data agents integrate LLM-driven reasoning with relational data access, executable analytical tools, and multi-step workflow orchestration, making them increasingly central to ente…
HMAF: A Hierarchical Multi-Slot GD-RTB Allocation Framework
Tianxing Bu, Zhaoqi Zhang, Linyou Cai +7
In modern online advertising platforms, Guaranteed Delivery (GD) contracts coexist and bid with Real-Time Bidding (RTB) auctions. Recent approaches either decouple GD and RTB optim…
CausalPOI: Spatio-Temporal Graph-Based Causal Modeling for Cold-Start POI Check-in Forecasting
Zhaoqi Zhang, Miao Xie, Yi Li +3
As urban environments continue to evolve rapidly, accurately modeling the dynamic behaviour of Points of Interest is essential for supporting data-driven urban planning and commerc…
BBC: Improving Large-k Approximate Nearest Neighbor Search with a Bucket-based Result Collector
Ziqi Yin, Gao Cong, Kai Zeng +2
Although Approximate Nearest Neighbor (ANN) search has been extensively studied, large-k ANN queries that aim to retrieve a large number of nearest neighbors remain underexplored,…
Beyond Single Slot: Joint Optimization for Multi-Slot Guaranteed Display Advertising
Zhaoqi Zhang, Jiaming Deng, Miao Xie +5
Guaranteed display advertising is crucial for platform monetization, yet existing methods often operate under a single-slot assumption, limiting their ability to optimize allocatio…
FDABench: A Benchmark for Data Agents on Analytical Queries over Heterogeneous Data
Ziting Wang, Shize Zhang, Haitao Yuan +3
The growing demand for data-driven decision-making has created an urgent need for data agents that can reason over heterogeneous data (databases, documents, web content, images, vi…
A Modular Multitask Reasoning Framework Integrating Spatio-temporal Models and LLMs
Kethmi Hirushini Hettige, Jiahao Ji, Cheng Long +3
Spatio-temporal data mining plays a pivotal role in informed decision making across diverse domains. However, existing models are often restricted to narrow tasks, lacking the capa…
BMTree: Designing, Learning, and Updating Piecewise Space-Filling Curves for Multi-Dimensional Data Indexing
Jiangneng Li, Yuang Liu, Zheng Wang +5
Space-filling curves (SFC, for short) have been widely applied to index multi-dimensional data, which first maps the data to one dimension, and then a one-dimensional indexing meth…
Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey
Yuxuan Liang, Haomin Wen, Yutong Xia +6
Spatio-Temporal (ST) data science, which includes sensing, managing, and mining large-scale data across space and time, is fundamental to understanding complex systems in domains s…
DEG: Efficient Hybrid Vector Search Using the Dynamic Edge Navigation Graph
Ziqi Yin, Jianyang Gao, Pasquale Balsebre +2
Bimodal data, such as image-text pairs, has become increasingly prevalent in the digital era. The Hybrid Vector Query (HVQ) is an effective approach for querying such data and has…
Self-Supervised Representation Learning for Geospatial Objects: A Survey
Yile Chen, Weiming Huang, Kaiqi Zhao +2
The proliferation of various data sources in urban and territorial environments has significantly facilitated the development of geospatial artificial intelligence (GeoAI) across a…
UrbanLLM: Autonomous Urban Activity Planning and Management with Large Language Models
Yue Jiang, Qin Chao, Yile Chen +3
Location-based services play an critical role in improving the quality of our daily lives. Despite the proliferation of numerous specialized AI models within spatio-temporal contex…
SAGDFN: A Scalable Adaptive Graph Diffusion Forecasting Network for Multivariate Time Series Forecasting
Yue Jiang, Xiucheng Li, Yile Chen +4
Time series forecasting is essential for our daily activities and precise modeling of the complex correlations and shared patterns among multiple time series is essential for impro…
Road Network Representation Learning with the Third Law of Geography
Haicang Zhou, Weiming Huang, Yile Chen +3
Road network representation learning aims to learn compressed and effective vectorized representations for road segments that are applicable to numerous tasks. In this paper, we id…
LLM-R2: A Large Language Model Enhanced Rule-based Rewrite System for Boosting Query Efficiency
Zhaodonghui Li, Haitao Yuan, Huiming Wang +2
Query rewrite, which aims to generate more efficient queries by altering a SQL query's structure without changing the query result, has been an important research problem. In order…
Semantic-Enhanced Representation Learning for Road Networks with Temporal Dynamics
Yile Chen, Xiucheng Li, Gao Cong +2
In this study, we introduce a novel framework called Toast for learning general-purpose representations of road networks, along with its advanced counterpart DyToast, designed to e…
LAMP: A Language Model on the Map
Pasquale Balsebre, Weiming Huang, Gao Cong
Large Language Models (LLMs) are poised to play an increasingly important role in our lives, providing assistance across a wide array of tasks. In the geospatial domain, LLMs have…
LIST: Learning to Index Spatio-Textual Data for Embedding based Spatial Keyword Queries
Ziqi Yin, Shanshan Feng, Shang Liu +3
With the proliferation of spatio-textual data, Top-k KNN spatial keyword queries (TkQs), which return a list of objects based on a ranking function that considers both spatial and…
AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction
Kethmi Hirushini Hettige, Jiahao Ji, Shili Xiang +3
Air quality prediction and modelling plays a pivotal role in public health and environment management, for individuals and authorities to make informed decisions. Although traditio…
AdapTraj: A Multi-Source Domain Generalization Framework for Multi-Agent Trajectory Prediction
Tangwen Qian, Yile Chen, Gao Cong +2
Multi-agent trajectory prediction, as a critical task in modeling complex interactions of objects in dynamic systems, has attracted significant research attention in recent years.…