674 citations
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7 papers · 1 filter
Dynamic Causal Collaborative Filtering
Shuyuan Xu, Juntao Tan, Zuohui Fu +3
Causal graph, as an effective and powerful tool for causal modeling, is usually assumed as a Directed Acyclic Graph (DAG). However, recommender systems usually involve feedback loo…
Interactive Model Cards: A Human-Centered Approach to Model Documentation
Anamaria Crisan, Margaret Drouhard, Jesse Vig +1
Deep learning models for natural language processing (NLP) are increasingly adopted and deployed by analysts without formal training in NLP or machine learning (ML). However, the d…
Mining Root Cause Knowledge from Cloud Service Incident Investigations for AIOps
Amrita Saha, Steven C. H. Hoi
Root Cause Analysis (RCA) of any service-disrupting incident is one of the most critical as well as complex tasks in IT processes, especially for cloud industry leaders like Salesf…
iSEA: An Interactive Pipeline for Semantic Error Analysis of NLP Models
Jun Yuan, Jesse Vig, Nazneen Rajani
Error analysis in NLP models is essential to successful model development and deployment. One common approach for diagnosing errors is to identify subpopulations in the dataset whe…
Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network
Liangwei Yang, Zhiwei Liu, Yu Wang +3
Because of the large number of online games available nowadays, online game recommender systems are necessary for users and online game platforms. The former can discover more pote…
Intent Contrastive Learning for Sequential Recommendation
Yongjun Chen, Zhiwei Liu, Jia Li +2
Users' interactions with items are driven by various intents (e.g., preparing for holiday gifts, shopping for fishing equipment, etc.).However, users' underlying intents are often…