Yang Song

Orcid: 0000-0002-1714-5527

Affiliations:
  • Kuaishou Technology, Beijing, China
  • Google Research, Kirkland, WA, USA
  • Microsoft Research, Redmond, WA, USA
  • Pennsylvania State University, School of Electrical Engineering and Computer Science, University Park, PA, USA


According to our database1, Yang Song authored at least 89 papers between 2005 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Pyramidal Flow Matching for Efficient Video Generative Modeling.
CoRR, 2024

Beyond Relevance: Improving User Engagement by Personalization for Short-Video Search.
CoRR, 2024

DimeRec: A Unified Framework for Enhanced Sequential Recommendation via Generative Diffusion Models.
CoRR, 2024

RectifID: Personalizing Rectified Flow with Anchored Classifier Guidance.
CoRR, 2024

Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems.
Proceedings of the ACM on Web Conference 2024, 2024

The 2nd Workshop on Recommendation with Generative Models.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Inverse Learning with Extremely Sparse Feedback for Recommendation.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Mixed Attention Network for Cross-domain Sequential Recommendation.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

To Search or to Recommend: Predicting Open-App Motivation with Neural Hawkes Process.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

UniSAR: Modeling User Transition Behaviors between Search and Recommendation.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

A Self-boosted Framework for Calibrated Ranking.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Contextual Distillation Model for Diversified Recommendation.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

GradCraft: Elevating Multi-task Recommendations through Holistic Gradient Crafting.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Incorporating Dynamic Temperature Estimation into Contrastive Learning on Graphs.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

SAQRec: Aligning Recommender Systems to User Satisfaction via Questionnaire Feedback.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Large Language Models Enhanced Collaborative Filtering.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

TWIN V2: Scaling Ultra-Long User Behavior Sequence Modeling for Enhanced CTR Prediction at Kuaishou.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
Enhancing Recommendation with Search Data in a Causal Learning Manner.
ACM Trans. Inf. Syst., October, 2023

Generative Retrieval with Semantic Tree-Structured Item Identifiers via Contrastive Learning.
CoRR, 2023

PANE-GNN: Unifying Positive and Negative Edges in Graph Neural Networks for Recommendation.
CoRR, 2023

Dual-interest Factorization-heads Attention for Sequential Recommendation.
Proceedings of the ACM Web Conference 2023, 2023

Multi-behavior Self-supervised Learning for Recommendation.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Graph Contrastive Learning with Generative Adversarial Network.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

PEPNet: Parameter and Embedding Personalized Network for Infusing with Personalized Prior Information.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

TWIN: TWo-stage Interest Network for Lifelong User Behavior Modeling in CTR Prediction at Kuaishou.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Instant Representation Learning for Recommendation over Large Dynamic Graphs.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Leveraging Watch-time Feedback for Short-Video Recommendations: A Causal Labeling Framework.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

KuaiSAR: A Unified Search And Recommendation Dataset.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Learning and Optimization of Implicit Negative Feedback for Industrial Short-video Recommender System.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

SHARK: A Lightweight Model Compression Approach for Large-scale Recommender Systems.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
HybridGNN: Learning Hybrid Representation in Multiplex Heterogeneous Networks.
CoRR, 2022

Disentangling Long and Short-Term Interests for Recommendation.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

A Model-Agnostic Causal Learning Framework for Recommendation using Search Data.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

When Multi-Level Meets Multi-Interest: A Multi-Grained Neural Model for Sequential Recommendation.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Query Prior Matters: A MRC Framework for Multimodal Named Entity Recognition.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

E-ConvRec: A Large-Scale Conversational Recommendation Dataset for E-Commerce Customer Service.
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

HybridGNN: Learning Hybrid Representation for Recommendation in Multiplex Heterogeneous Networks.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Billion-user Customer Lifetime Value Prediction: An Industrial-scale Solution from Kuaishou.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
Sequential Recommendation with Graph Neural Networks.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Concept-Aware Denoising Graph Neural Network for Micro-Video Recommendation.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Enhancing Multi-turn Dialogue Modeling with Intent Information for E-Commerce Customer Service.
Proceedings of the Natural Language Processing and Chinese Computing, 2020

2019
Automated Thematic and Emotional Modern Chinese Poetry Composition.
Proceedings of the Natural Language Processing and Chinese Computing, 2019

2016
Query-Less: Predicting Task Repetition for NextGen Proactive Search and Recommendation Engines.
Proceedings of the 25th International Conference on World Wide Web, 2016

Multi-Rate Deep Learning for Temporal Recommendation.
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016

Modeling User Interests for Zero-Query Ranking.
Proceedings of the Advances in Information Retrieval, 2016

Large-Scale Analysis of Viewing Behavior: Towards Measuring Satisfaction with Mobile Proactive Systems.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

Exploring Multiple Feature Spaces for Novel Entity Discovery.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
An Overview of Microsoft Academic Service (MAS) and Applications.
Proceedings of the 24th International Conference on World Wide Web Companion, 2015

A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems.
Proceedings of the 24th International Conference on World Wide Web, 2015

Robust and distributed web-scale near-dup document conflation in microsoft academic service.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014
Task Trail: An Effective Segmentation of User Search Behavior.
IEEE Trans. Knowl. Data Eng., 2014

Online behavioral genome sequencing from usage logs: decoding the search behaviors.
Proceedings of the 23rd International World Wide Web Conference, 2014

Adapting deep RankNet for personalized search.
Proceedings of the Seventh ACM International Conference on Web Search and Data Mining, 2014

Modeling action-level satisfaction for search task satisfaction prediction.
Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2014

Context-aware web search abandonment prediction.
Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2014

2013
Enhancing personalized search by mining and modeling task behavior.
Proceedings of the 22nd International World Wide Web Conference, 2013

Learning to extract cross-session search tasks.
Proceedings of the 22nd International World Wide Web Conference, 2013

Evaluating and predicting user engagement change with degraded search relevance.
Proceedings of the 22nd International World Wide Web Conference, 2013

Exploring and exploiting user search behavior on mobile and tablet devices to improve search relevance.
Proceedings of the 22nd International World Wide Web Conference, 2013

Personalized ranking model adaptation for web search.
Proceedings of the 36th International ACM SIGIR conference on research and development in Information Retrieval, 2013

2012
Hierarchical Online Problem Classification for IT Support Services.
IEEE Trans. Serv. Comput., 2012

Evaluating the effectiveness of search task trails.
Proceedings of the 21st World Wide Web Conference 2012, 2012

Query suggestion by constructing term-transition graphs.
Proceedings of the Fifth International Conference on Web Search and Web Data Mining, 2012

2011
Automatic tag recommendation algorithms for social recommender systems.
ACM Trans. Web, 2011

Searchable web sites recommendation.
Proceedings of the Forth International Conference on Web Search and Web Data Mining, 2011

Post-ranking query suggestion by diversifying search results.
Proceedings of the Proceeding of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2011

Hierarchical tag visualization and application for tag recommendations.
Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

A task level metric for measuring web search satisfaction and its application on improving relevance estimation.
Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

2010
Optimal rare query suggestion with implicit user feedback.
Proceedings of the 19th International Conference on World Wide Web, 2010

2009
Better Naive Bayes classification for high-precision spam detection.
Softw. Pract. Exp., 2009

ERMIS: Designing, developing, and delivering a remote managed infrastructure services solution.
IBM J. Res. Dev., 2009

Problem classification method to enhance the ITIL incident and problem.
Proceedings of the Integrated Network Management, 2009

2008
Real-time automatic tag recommendation.
Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2008

Efficient user preference predictions using collaborative filtering.
Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

A Non-parametric Approach to Pair-Wise Dynamic Topic Correlation Detection.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

A sparse gaussian processes classification framework for fast tag suggestions.
Proceedings of the 17th ACM Conference on Information and Knowledge Management, 2008

2007
Social Bookmarking for Scholarly Digital Libraries.
IEEE Internet Comput., 2007

Generative models for name disambiguation.
Proceedings of the 16th International Conference on World Wide Web, 2007

Efficient Multiclass Boosting Classification with Active Learning.
Proceedings of the Seventh SIAM International Conference on Data Mining, 2007

IKNN: Informative K-Nearest Neighbor Pattern Classification.
Proceedings of the Knowledge Discovery in Databases: PKDD 2007, 2007

Efficient topic-based unsupervised name disambiguation.
Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, 2007

Evaluating tagging behavior in social bookmarking systems: metrics and design heuristics.
Proceedings of the 2007 International ACM SIGGROUP Conference on Supporting Group Work, 2007

2006
CiteSeer<sup>chi</sup>: a scalable autonomous scientific digital library.
Proceedings of the 1st International Conference on Scalable Information Systems, 2006

Boosting the Feature Space: Text Classification for Unstructured Data on the Web.
Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006

2005
Towards discovering organizational structure from email corpus.
Proceedings of the Fourth International Conference on Machine Learning and Applications, 2005


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