50 citations · 98 across the 10 of their papers we have counts for
10 papers
PromptST: Prompt-Enhanced Spatio-Temporal Multi-Attribute Prediction
Zijian Zhang, Xiangyu Zhao, Qidong Liu +6
In the era of information explosion, spatio-temporal data mining serves as a critical part of urban management. Considering the various fields demanding attention, e.g., traffic st…
XFlow: Benchmarking Flow Behaviors over Graphs
Zijian Zhang, Zonghan Zhang, Zhiqian Chen
The occurrence of diffusion on a graph is a prevalent and significant phenomenon, as evidenced by the spread of rumors, influenza-like viruses, smart grid failures, and similar eve…
ClickINC: In-network Computing as a Service in Heterogeneous Programmable Data-center Networks
Wenquan Xu, Zijian Zhang, Yong Feng +8
In-Network Computing (INC) has found many applications for performance boosts or cost reduction. However, given heterogeneous devices, diverse applications, and multi-path network…
When Federated Recommendation Meets Cold-Start Problem: Separating Item Attributes and User Interactions
Chunxu Zhang, Guodong Long, Tianyi Zhou +3
Federated recommendation system usually trains a global model on the server without direct access to users' private data on their own devices. However, this separation of the recom…
AutoSTL: Automated Spatio-Temporal Multi-Task Learning
Zijian Zhang, Xiangyu Zhao, Hao Miao +3
Spatio-Temporal prediction plays a critical role in smart city construction. Jointly modeling multiple spatio-temporal tasks can further promote an intelligent city life by integra…
Dual Personalization on Federated Recommendation
Chunxu Zhang, Guodong Long, Tianyi Zhou +4
Federated recommendation is a new Internet service architecture that aims to provide privacy-preserving recommendation services in federated settings. Existing solutions are used t…
Explainable Information Retrieval: A Survey
Avishek Anand, Lijun Lyu, Maximilian Idahl +3
Explainable information retrieval is an emerging research area aiming to make transparent and trustworthy information retrieval systems. Given the increasing use of complex machine…
SparCAssist: A Model Risk Assessment Assistant Based on Sparse Generated Counterfactuals
Zijian Zhang, Vinay Setty, Avishek Anand
We introduce SparcAssist, a general-purpose risk assessment tool for the machine learning models trained for language tasks. It evaluates models' risk by inspecting their behavior…
Dissonance Between Human and Machine Understanding
Zijian Zhang, Jaspreet Singh, Ujwal Gadiraju +1
Complex machine learning models are deployed in several critical domains including healthcare and autonomous vehicles nowadays, albeit as functional black boxes. Consequently, ther…
Asynchronous Training of Word Embeddings for Large Text Corpora
Avishek Anand, Megha Khosla, Jaspreet Singh +2
Word embeddings are a powerful approach for analyzing language and have been widely popular in numerous tasks in information retrieval and text mining. Training embeddings over hug…