本文整理了KDD21的Accepted Papers^[1]中，工业界在搜索、推荐、广告、nlp上的文章。整理的论文列表比较偏个人口味，选取的方式是根据论文作者列表上看是否是公司主导的，但判断比较偏主观，存在漏掉的可能。盘点的方式主要按照公司和方向来划分，排名不计先后顺序。

1. 按照方向分类

主要挑选了一些笔者比较感兴趣的方向，并整理了对应的文章名称。读者可以大致读一下文章名，判断是否和自己的研究方向或工作方向一致，从中选择感兴趣的文章进行精读。

1.1 推荐系统

1.1.1 样本

涉及到采样、负样本等。

Google: Bootstrapping for Batch Active Sampling
Google: Bootstrapping Recommendations at Chrome Web Store
Alibaba：Real Negatives Matter: Continuous Training with Real Negatives for Delayed Feedback Modeling

1.1.2 表征学习

Google: Learning to Embed Categorical Features without Embedding Tables for Recommendation
华为：An Embedding Learning Framework for Numerical Features in CTR Prediction
腾讯：Learning Reliable User Representations from Volatile and Sparse Data to Accurately Predict Customer Lifetime Value
阿里：Representation Learning for Predicting Customer Orders

1.1.3 跨域推荐

阿里：Debiasing Learning based Cross-domain Recommendation
腾讯：Adversarial Feature Translation for Multi-domain Recommendation

1.1.4 纠偏

阿里：Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems
阿里：Debiasing Learning based Cross-domain Recommendation

1.1.5 图神经网络

华为：Dual Graph enhanced Embedding Neural Network for CTR Prediction
美团：Signed Graph Neural Network with Latent Groups
阿里：DMBGN: Deep Multi-Behavior Graph Networks for Voucher Redemption Rate Prediction
百度：MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal

1.1.6 多任务

Google：Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning
美团：Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning for Customer Acquisition
百度：MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal

1.1.7 多模态

阿里：SEMI: A Sequential Multi-Modal Information Transfer Network for E-Commerce Micro-Video Recommendations

1.1.8 知识图谱

Microsoft：Reinforced Anchor Knowledge Graph Generation for News Recommendation Reasoning

1.1.9 推荐系统架构

Facebook：Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism
Facebook：Hierarchical Training: Scaling Deep Recommendation Models on Large CPU Clusters
阿里，FleetRec: Large-Scale Recommendation Inference on Hybrid GPU-FPGA Clusters
腾讯，Large-Scale Network Embedding in Apache Spark
Microsoft，On Post-Selection Inference in A/B Testing

1.2 搜索

1.2.1 向量检索

阿里：Embedding-based Product Retrieval in Taobao Search

1.2.2 查询/内容理解

Facebook：Que2Search: Fast and Accurate Query and Document Understanding for Search at Facebook

1.2.3 概念图谱

阿里巴巴：AliCG: Fine-grained and Evolvable Conceptual Graph Construction for Semantic Search at Alibaba
阿里巴巴：AliCoCo2: Commonsense Knowledge Extraction, Representation and Application in E-commerce

1.2.4 预训练

百度：Pretrained Language Models for Web-scale Retrieval in Baidu Search
微软：Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature

1.2.5 Query改写/自动补全

微软：Diversity driven Query Rewriting in Search Advertising
百度：Meta-Learned Spatial-Temporal POI Auto-Completion for the Search Engine at Baidu Maps

1.2.6 图神经网络

百度：HGAMN: Heterogeneous Graph Attention Matching Network for Multilingual POI Retrieval at Baidu Maps

1.2.7 多模态

Google: Mondegreen: A Post-Processing Solution to Speech Recognition Error Correction for Voice Search Queries
Facebook：VisRel: Media Search at Scale

1.2.8 边缘计算

阿里：FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data

1.2.9 搜索引擎架构

百度：Norm Adjusted Proximity Graph for Fast Inner Product Retrieval
百度：JIZHI: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu

1.3 广告

这一块文章不是很多，就不细分了。

Google: Clustering for Private Interest-based Advertising
阿里：A Unified Solution to Constrained Bidding in Online Display Advertising
阿里：Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning
阿里：Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertising
阿里：We Know What You Want: An Advertising Strategy Recommender System for Online Advertising

1.4 NLP

1.4.1 预训练

微软：NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search
阿里：M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining
微软：TUTA: Tree-based Transformers for Generally Structured Table Pre-training

1.4.2 命名实体识别

微软：Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition

1.4.3 少样本学习

微软：Generalized Zero-Shot Extreme Multi-label Learning
微软：Zero-shot Multi-lingual Interrogative Question Generation for “People Also Ask” at Bing

1.4.4 摘要

微软：Reinforcing Pretrained Models for Generating Attractive Text Advertisements

1.4.5 意图识别

阿里：MeLL: Large-scale Extensible User Intent Classification for Dialogue Systems with Meta Lifelong Learning

1.4.6 多模态

阿里：M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining

2.按照公司分类

2.1 Google

Learning to Embed Categorical Features without Embedding Tables for Recommendation
NewsEmbed: Modeling News through Pre-trained Document Representations
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning
Bootstrapping for Batch Active Sampling
Bootstrapping Recommendations at Chrome Web Store
Clustering for Private Interest-based Advertising
Dynamic Language Models for Continuously Evolving Content
Mondegreen: A Post-Processing Solution to Speech Recognition Error Correction for Voice Search Queries
On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition

2.2 Facebook

Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism
Preference Amplification in Recommender Systems
Hierarchical Training: Scaling Deep Recommendation Models on Large CPU Clusters
Network Experimentation at Scale
Que2Search: Fast and Accurate Query and Document Understanding for Search at Facebook
VisRel: Media Search at Scale
Balancing Consistency and Disparity in Network Alignment

2.3 Microsoft

Generalized Zero-Shot Extreme Multi-label Learning
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search
Reinforced Anchor Knowledge Graph Generation for News Recommendation Reasoning
Table2Charts: Recommending Charts by Learning Shared Table Representations
TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Data
TUTA: Tree-based Transformers for Generally Structured Table Pre-training
Contextual Bandit Applications in a Customer Support Bot
Diversity driven Query Rewriting in Search Advertising
Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature
On Post-Selection Inference in A/B Testing
Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition
Reinforcing Pretrained Models for Generating Attractive Text Advertisements
Zero-shot Multi-lingual Interrogative Question Generation for “People Also Ask” at Bing

2.4 阿里

A Unified Solution to Constrained Bidding in Online Display Advertising
AliCG: Fine-grained and Evolvable Conceptual Graph Construction for Semantic Search at Alibaba
AliCoCo2: Commonsense Knowledge Extraction, Representation and Application in E-commerce
Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems
Debiasing Learning based Cross-domain Recommendation
Device-Cloud Collaborative Learning for Recommendation
Deep Inclusion Relation-aware Network for User Response Prediction at Fliggy
DMBGN: Deep Multi-Behavior Graph Networks for Voucher Redemption Rate Prediction
Dual Attentive Sequential Learning for Cross-Domain Click-Through Rate Prediction
Embedding-based Product Retrieval in Taobao Search
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning
FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data
FleetRec: Large-Scale Recommendation Inference on Hybrid GPU-FPGA Clusters
Intention-aware Heterogeneous Graph Attention Networks for Fraud Transactions Detection
Live-Streaming Fraud Detection: A Heterogeneous Graph Neural Network Approach
M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining
Markdowns in E-Commerce Fresh Retail: A Counterfactual Prediction and Multi-Period Optimization Approach
MeLL: Large-scale Extensible User Intent Classification for Dialogue Systems with Meta Lifelong Learning
Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search
Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertising
Real Negatives Matter: Continuous Training with Real Negatives for Delayed Feedback Modeling
Representation Learning for Predicting Customer Orders
SEMI: A Sequential Multi-Modal Information Transfer Network for E-Commerce Micro-Video Recommendations
We Know What You Want: An Advertising Strategy Recommender System for Online Advertising

2.5 百度

Norm Adjusted Proximity Graph for Fast Inner Product Retrieval
Curriculum Meta-Learning for Next POI Recommendation
Pretrained Language Models for Web-scale Retrieval in Baidu Search
HGAMN: Heterogeneous Graph Attention Matching Network for Multilingual POI Retrieval at Baidu Maps
JIZHI: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu
Meta-Learned Spatial-Temporal POI Auto-Completion for the Search Engine at Baidu Maps
MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal
SSML: Self-Supervised Meta-Learner for En Route Travel Time Estimation at Baidu Maps
Talent Demand Forecasting with Attentive Neural Sequential Model

2.6 腾讯

Why Attentions May Not Be Interpretable?
Adversarial Feature Translation for Multi-domain Recommendation
Large-Scale Network Embedding in Apache Spark
Learn to Expand Audience via Meta Hybrid Experts and Critics
Learning Reliable User Representations from Volatile and Sparse Data to Accurately Predict Customer Lifetime Value

2.7 美团

Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning for Customer Acquisition
User Consumption Intention Prediction in Meituan
Signed Graph Neural Network with Latent Groups
A Deep Learning Method for Route and Time Prediction in Food Delivery Service

2.8 华为

An Embedding Learning Framework for Numerical Features in CTR Prediction
Dual Graph enhanced Embedding Neural Network for CTR Prediction
Discrete-time Temporal Network Embedding via Implicit Hierarchical Learning
Retrieval & Interaction Machine for Tabular Data Prediction
A Multi-Graph Attributed Reinforcement Learning Based Optimization Algorithm for Large-scale Hybrid Flow Shop Scheduling Problem