Kun Gai

Orcid: 0000-0002-3636-3618

According to our database1, Kun Gai authored at least 110 papers between 2008 and 2024.

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

Timeline

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Bibliography

2024
ERABAL: Enhancing Role-Playing Agents through Boundary-Aware Learning.
CoRR, 2024

HoME: Hierarchy of Multi-Gate Experts for Multi-Task Learning at Kuaishou.
CoRR, 2024

Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction.
CoRR, 2024

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

Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial Application.
CoRR, 2024

M3oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Framework.
CoRR, 2024

RecGPT: Generative Personalized Prompts for Sequential Recommendation via ChatGPT Training Paradigm.
CoRR, 2024

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

Enhancing Interpretability and Effectiveness in Recommendation with Numerical Features via Learning to Contrast the Counterfactual samples.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Enhancing Recommendation Accuracy and Diversity with Box Embedding: A Universal Framework.
Proceedings of the ACM on Web Conference 2024, 2024

Adaptive Neural Ranking Framework: Toward Maximized Business Goal for Cascade Ranking Systems.
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

M<sup>3</sup>oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Framework.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Sequential Recommendation for Optimizing Both Immediate Feedback and Long-term Retention.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Modeling User Fatigue for Sequential Recommendation.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

RPAF: A Reinforcement Prediction-Allocation Framework for Cache Allocation in Large-Scale Recommender Systems.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

A Multi-modal Modeling Framework for Cold-start Short-video Recommendation.
Proceedings of the 18th ACM Conference on Recommender Systems, 2024

DialogBench: Evaluating LLMs as Human-like Dialogue Systems.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Tag Tree-Guided Multi-grained Alignment for Multi-Domain Short Video Recommendation.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Future Impact Decomposition in Request-level Recommendations.
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

Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Inductive-Deductive Strategy Reuse for Multi-Turn Instructional Dialogues.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Small Agent Can Also Rock! Empowering Small Language Models as Hallucination Detector.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Decoding at the Speed of Thought: Harnessing Parallel Decoding of Lexical Units for LLMs.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 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

A Self-Adaptive Fairness Constraint Framework for Industrial Recommender System.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Missing Interest Modeling with Lifelong User Behavior Data for Retrieval Recommendation.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Parrot: Enhancing Multi-Turn Instruction Following for Large Language Models.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Just Ask One More Time! Self-Agreement Improves Reasoning of Language Models in (Almost) All Scenarios.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Ask One More Time: Self-Agreement Improves Reasoning of Language Models in (Almost) All Scenarios.
CoRR, 2023

DialogBench: Evaluating LLMs as Human-like Dialogue Systems.
CoRR, 2023

KwaiYiiMath: Technical Report.
CoRR, 2023

Parrot: Enhancing Multi-Turn Chat Models by Learning to Ask Questions.
CoRR, 2023

AdaRec: Adaptive Sequential Recommendation for Reinforcing Long-term User Engagement.
CoRR, 2023

Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization.
CoRR, 2023

A Large Language Model Enhanced Conversational Recommender System.
CoRR, 2023

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

Disentangled Causal Embedding With Contrastive Learning For Recommender System.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Divide and Conquer: Towards Better Embedding-based Retrieval for Recommender Systems from a Multi-task Perspective.
Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Multi-Task Recommendations with Reinforcement Learning.
Proceedings of the ACM Web Conference 2023, 2023

Exploration and Regularization of the Latent Action Space in Recommendation.
Proceedings of the ACM Web Conference 2023, 2023

Two-Stage Constrained Actor-Critic for Short Video Recommendation.
Proceedings of the ACM Web Conference 2023, 2023

Reinforcing User Retention in a Billion Scale Short Video Recommender System.
Proceedings of the Companion 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

KuaiSim: A Comprehensive Simulator for Recommender Systems.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

State Regularized Policy Optimization on Data with Dynamics Shift.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PrefRec: Recommender Systems with Human Preferences for Reinforcing Long-term User Engagement.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 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

Generative Flow Network for Listwise Recommendation.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

A Multi-Agent Framework for Recommendation with Heterogeneous Sources.
Proceedings of the International Joint Conference on Neural Networks, 2023

ResAct: Reinforcing Long-term Engagement in Sequential Recommendation with Residual Actor.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Deconfounding Duration Bias in Watch-time Prediction for Video Recommendation.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Real-time Short Video Recommendation on Mobile Devices.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
Truncation-Free Matching System for Display Advertising at Alibaba.
CoRR, 2021

Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising.
Proceedings of the WSDM '21, 2021

Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning.
CoRR, 2020

CAN: Revisiting Feature Co-Action for Click-Through Rate Prediction.
CoRR, 2020

COLD: Towards the Next Generation of Pre-Ranking System.
CoRR, 2020

DCAF: A Dynamic Computation Allocation Framework for Online Serving System.
CoRR, 2020

A Deep Recurrent Survival Model for Unbiased Ranking.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Calibrating User Response Predictions in Online Advertising.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track, 2020

Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Learning Optimal Tree Models under Beam Search.
Proceedings of the 37th International Conference on Machine Learning, 2020

Dynamic Knapsack Optimization Towards Efficient Multi-Channel Sequential Advertising.
Proceedings of the 37th International Conference on Machine Learning, 2020

Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Learning to Infer User Hidden States for Online Sequential Advertising.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

A Deep Prediction Network for Understanding Advertiser Intent and Satisfaction.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Sequential Advertising Agent with Interpretable User Hidden Intents.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Progressive Feature Polishing Network for Salient Object Detection.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Res-embedding for Deep Learning Based Click-Through Rate Prediction Modeling.
CoRR, 2019

Lifelong Sequential Modeling with Personalized Memorization for User Response Prediction.
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Joint Optimization of Tree-based Index and Deep Model for Recommender Systems.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Bid Optimization by Multivariable Control in Display Advertising.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Improve Diverse Text Generation by Self Labeling Conditional Variational Auto Encoder.
Proceedings of the IEEE International Conference on Acoustics, 2019

Stick to the Facts: Learning towards a Fidelity-oriented E-Commerce Product Description Generation.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Learning Adaptive Display Exposure for Real-Time Advertising.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Learning to Advertise for Organic Traffic Maximization in E-Commerce Product Feeds.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Deep Interest Evolution Network for Click-Through Rate Prediction.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
A Multi-Agent Reinforcement Learning Method for Impression Allocation in Online Display Advertising.
CoRR, 2018

Learning to Advertise with Adaptive Exposure via Constrained Two-Level Reinforcement Learning.
CoRR, 2018

Budget Constrained Bidding by Model-free Reinforcement Learning in Display Advertising.
CoRR, 2018

Learning Tree-based Deep Model for Recommender Systems.
CoRR, 2018

Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate.
Proceedings of the 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, 2018

Semantic Human Matting.
Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018

Learning Tree-based Deep Model for Recommender Systems.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Deep Interest Network for Click-Through Rate Prediction.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Budget Constrained Bidding by Model-free Reinforcement Learning in Display Advertising.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Real-Time Bidding with Multi-Agent Reinforcement Learning in Display Advertising.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Image Matters: Visually Modeling User Behaviors Using Advanced Model Server.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Rocket Launching: A Universal and Efficient Framework for Training Well-Performing Light Net.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Image Matters: Jointly Train Advertising CTR Model with Image Representation of Ad and User Behavior.
CoRR, 2017

Deep Interest Network for Click-Through Rate Prediction.
CoRR, 2017

Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction.
CoRR, 2017

Optimized Cost per Click in Taobao Display Advertising.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2013
Efficient blind separation of reflection layers with nonparametric transformations.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Blind Separation of Superimposed Moving Images Using Image Statistics.
IEEE Trans. Pattern Anal. Mach. Intell., 2012

Efficient Superimposition Recovering Algorithm
CoRR, 2012

2011
Efficient Euclidean projections via Piecewise Root Finding and its application in gradient projection.
Neurocomputing, 2011

2010
Learning Kernels with Radiuses of Minimum Enclosing Balls.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Learning Discriminative Piecewise Linear Models with Boundary Points.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
Blind separation of superimposed images with unknown motions.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

2008
Blindly separating mixtures of multiple layers with spatial shifts.
Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008


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