activity
20222025
most citedCausalMMM: Learning Causal Structure for Marketing Mix Modeling

9 citations · 19 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2025

GTool: Graph Enhanced Tool Planning with Large Language Model

Wenjie Chen, Wenbin Li, Di Yao +3

Tool planning with large language models (LLMs), referring to selecting, organizing, and preparing the tools necessary to complete a user request, bridges the gap between natural l…

cs.LG2024

CausalTAD: Causal Implicit Generative Model for Debiased Online Trajectory Anomaly Detection

Wenbin Li, Di Yao, Chang Gong +6

Trajectory anomaly detection, aiming to estimate the anomaly risk of trajectories given the Source-Destination (SD) pairs, has become a critical problem for many real-world applica…

cs.AI2024

PORCA: Root Cause Analysis with Partially Observed Data

Chang Gong, Di Yao, Jin Wang +6

Root Cause Analysis (RCA) aims at identifying the underlying causes of system faults by uncovering and analyzing the causal structure from complex systems. It has been widely used…

cs.CL2024★ 2 cited

STBench: Assessing the Ability of Large Language Models in Spatio-Temporal Analysis

Wenbin Li, Di Yao, Ruibo Zhao +7

The rapid evolution of large language models (LLMs) holds promise for reforming the methodology of spatio-temporal data mining. However, current works for evaluating the spatio-tem…

cs.AI2024★ 9 cited

CausalMMM: Learning Causal Structure for Marketing Mix Modeling

Chang Gong, Di Yao, Lei Zhang +4

In online advertising, marketing mix modeling (MMM) is employed to predict the gross merchandise volume (GMV) of brand shops and help decision-makers to adjust the budget allocatio…

cs.LG2023★ 7 cited

Causal Discovery from Temporal Data: An Overview and New Perspectives

Chang Gong, Di Yao, Chuzhe Zhang +2

Temporal data, representing chronological observations of complex systems, has always been a typical data structure that can be widely generated by many domains, such as industry,…

cs.IR2022★ 1 cited

CausalMTA: Eliminating the User Confounding Bias for Causal Multi-touch Attribution

Di Yao, Chang Gong, Lei Zhang +2

Multi-touch attribution (MTA), aiming to estimate the contribution of each advertisement touchpoint in conversion journeys, is essential for budget allocation and automatically adv…