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09/14/2023
Neuro-Symbolic Recommendation Model based on Logic Query
A recommendation system assists users in finding items that are relevant...
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08/09/2023
Entire Space Cascade Delayed Feedback Modeling for Effective Conversion Rate Prediction
Conversion rate (CVR) prediction is an essential task for large-scale e-...
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07/11/2023
Neural-Symbolic Recommendation with Graph-Enhanced Information
The recommendation system is not only a problem of inductive statistics ...
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06/29/2023
Multi-Scenario Ranking with Adaptive Feature Learning
Recently, Multi-Scenario Learning (MSL) is widely used in recommendation...
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06/06/2023
Rec4Ad: A Free Lunch to Mitigate Sample Selection Bias for Ads CTR Prediction in Taobao
Click-Through Rate (CTR) prediction serves as a fundamental component in...
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06/06/2023
COPR: Consistency-Oriented Pre-Ranking for Online Advertising
Cascading architecture has been widely adopted in large-scale advertisin...
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05/22/2023
Capturing Conversion Rate Fluctuation during Sales Promotions: A Novel Historical Data Reuse Approach
Conversion rate (CVR) prediction is one of the core components in online...
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03/14/2023
Leveraging Pretrained Representations with Task-related Keywords for Alzheimer's Disease Detection
With the global population aging rapidly, Alzheimer's disease (AD) is pa...
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01/05/2023
HIT-SCIR at MMNLU-22: Consistency Regularization for Multilingual Spoken Language Understanding
Multilingual spoken language understanding (SLU) consists of two sub-tas...
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10/29/2022
Exploiting prompt learning with pre-trained language models for Alzheimer's Disease detection
Early diagnosis of Alzheimer's disease (AD) is crucial in facilitating p...
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10/13/2022
Sustainable Online Reinforcement Learning for Auto-bidding
Recently, auto-bidding technique has become an essential tool to increas...
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09/04/2022
Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Prediction Models
Deep learning techniques have been applied widely in industrial recommen...
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08/22/2022
KEEP: An Industrial Pre-Training Framework for Online Recommendation via Knowledge Extraction and Plugging
An industrial recommender system generally presents a hybrid list that c...
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08/12/2022
Joint Optimization of Ranking and Calibration with Contextualized Hybrid Model
Despite the development of ranking optimization techniques, the pointwis...
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06/20/2022
Adaptive Domain Interest Network for Multi-domain Recommendation
Industrial recommender systems usually hold data from multiple business ...
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06/02/2022
Learning Disentangled Representations for Counterfactual Regression via Mutual Information Minimization
Learning individual-level treatment effect is a fundamental problem in c...
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05/09/2022
Visual Encoding and Debiasing for CTR Prediction
Extracting expressive visual features is crucial for accurate Click-Thro...
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04/18/2022
StableMoE: Stable Routing Strategy for Mixture of Experts
The Mixture-of-Experts (MoE) technique can scale up the model size of Tr...
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04/11/2022
PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems
The development of personalized recommendation has significantly improve...
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04/04/2022
Dressi: A Hardware-Agnostic Differentiable Renderer with Reactive Shader Packing and Soft Rasterization
Differentiable rendering (DR) enables various computer graphics and comp...
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03/10/2022
BEAT: A Large-Scale Semantic and Emotional Multi-Modal Dataset for Conversational Gestures Synthesis
Achieving realistic, vivid, and human-like synthesized conversational ge...
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02/14/2022
Approximate Nearest Neighbor Search under Neural Similarity Metric for Large-Scale Recommendation
Model-based methods for recommender systems have been studied extensivel...
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02/14/2022
Asymptotically Unbiased Estimation for Delayed Feedback Modeling via Label Correction
Alleviating the delayed feedback problem is of crucial importance for th...
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02/09/2022
MBCT: Tree-Based Feature-Aware Binning for Individual Uncertainty Calibration
Most machine learning classifiers only concern classification accuracy, ...
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01/18/2022
Leaving No One Behind: A Multi-Scenario Multi-Task Meta Learning Approach for Advertiser Modeling
Advertisers play an essential role in many e-commerce platforms like Tao...
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12/21/2021
Adversarial Gradient Driven Exploration for Deep Click-Through Rate Prediction
Nowadays, data-driven deep neural models have already shown remarkable p...
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11/08/2021
Characterizing the adversarial vulnerability of speech self-supervised learning
A leaderboard named Speech processing Universal PERformance Benchmark (S...
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11/01/2021
Heterogeneous Graph Neural Networks for Large-Scale Bid Keyword Matching
Digital advertising is a critical part of many e-commerce platforms such...
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09/15/2021
Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training
Compared to monolingual models, cross-lingual models usually require a m...
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08/24/2021
Binary Code based Hash Embedding for Web-scale Applications
Nowadays, deep learning models are widely adopted in web-scale applicati...
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08/24/2021
Learning Effective and Efficient Embedding via an Adaptively-Masked Twins-based Layer
Embedding learning for categorical features is crucial for the deep lear...
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06/30/2021
Efficient Spatio-Temporal Recurrent Neural Network for Video Deblurring
Real-time video deblurring still remains a challenging task due to the c...
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06/15/2021
Consistency Regularization for Cross-Lingual Fine-Tuning
Fine-tuning pre-trained cross-lingual language models can transfer task-...
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06/11/2021
Improving Pretrained Cross-Lingual Language Models via Self-Labeled Word Alignment
The cross-lingual language models are typically pretrained with masked l...
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06/08/2021
Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search
Bid optimization for online advertising from single advertiser's perspec...
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05/17/2021
Towards a Better Tradeoff between Effectiveness and Efficiency in Pre-Ranking: A Learnable Feature Selection based Approach
In real-world search, recommendation, and advertising systems, the multi...
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03/11/2021
Tracking Air Pollution in China: Near Real-Time PM2.5 Retrievals from Multiple Data Sources
Air pollution has altered the Earth radiation balance, disturbed the eco...
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05/12/2020
Document Modeling with Graph Attention Networks for Multi-grained Machine Reading Comprehension
Natural Questions is a new challenging machine reading comprehension ben...
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10/28/2019
RPM-Oriented Query Rewriting Framework for E-commerce Keyword-Based Sponsored Search
Sponsored search optimizes revenue and relevance, which is estimated by ...
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02/24/2019
Aggregating E-commerce Search Results from Heterogeneous Sources via Hierarchical Reinforcement Learning
In this paper, we investigate the task of aggregating search results fro...
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10/08/2018
An AMR Aligner Tuned by Transition-based Parser
In this paper, we propose a new rich resource enhanced AMR aligner which...
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07/09/2018