KDD2023丨大模型论文合集

ACM SIGKDD（国际数据挖掘与知识发现大会，简称KDD）会议始于1989年，是数据挖掘领域历史最悠久、规模最大的国际顶级学术会议，也是首个引入大数据、数据科学、预测分析、众包等概念的会议，每年吸引了大量数据挖掘、机器学习、大数据和人工智能等领域的研究学者、从业人员参与。

AMiner通过AI技术，对 KDD2023 收录的会议论文进行了分类整理，今日分享的是大模型主题论文！（由于篇幅关系，本篇只展现部分论文，点击阅读原文可直达KDD顶会页面查看所有论文）

1.WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences

https://www.aminer.cn/pub/64893b17d68f896efa9826b7/

2.Pre-training Antibody Language Models for Antigen-Specific Computational Antibody Design

https://www.aminer.cn/pub/64af9a063fda6d7f065a6c00/

3.LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models

https://www.aminer.cn/pub/64af99fd3fda6d7f065a62f2/

4.JiuZhang 2.0: A Unified Chinese Pre-trained Language Model for Multi-task Mathematical Problem Solving

https://www.aminer.cn/pub/64af9a043fda6d7f065a6a45/

5.BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR Prediction

https://www.aminer.cn/pub/64af9a043fda6d7f065a69f8/

6.RecruitPro: A Pretrained Language Model with Skill-Aware Prompt Learning for Intelligent Recruitment

https://www.aminer.cn/pub/64af9a053fda6d7f065a6b09/

7.QUERT: Continual Pre-training of Language Model for Query Understanding in Travel Domain Search

https://www.aminer.cn/pub/6487e9fad68f896efa482b50/

8.Automated 3D Pre-Training for Molecular Property Prediction

https://www.aminer.cn/pub/64893b17d68f896efa982588/

9.GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation

https://www.aminer.cn/pub/63fec3cd90e50fcafdd70322/

10.CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X

https://www.aminer.cn/pub/64264f7b90e50fcafd68e145/

11.Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications

https://www.aminer.cn/pub/647eaf51d68f896efad41cdb/

12.Text Is All You Need: Learning Language Representations for Sequential Recommendation

https://www.aminer.cn/pub/646d863cd68f896efa09f2e5/

KDD顶会：https://www.aminer.cn/conf/5ea1b22bedb6e7d53c00c41b/KDD2023