Gandalf: Learning Label-label Correlations in Extreme Multi-label Classification via Label Features
Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis, Atmadeep Banerjee, Cho-Jui Hsieh, Rohit Babbar
KDD 2024 Papers
ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Decision breakdown
562papers
Counted from the official paper list; may differ slightly from the number the conference announced.
- Other / unlabeled562100.0%
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TitleTypeTopic
GRILLBot In Practice: Lessons and Tradeoffs Deploying Large Language Models for Adaptable Conversational Task Assistants
Sophie Fischer, Carlos Gemmell, Niklas Tecklenburg, Iain Mackie, Federico Rossetto, Jeffrey Dalton
GRAM: Generative Retrieval Augmented Matching of Data Schemas in the Context of Data Security
Xuanqing Liu, Runhui Wang, Yang Song, Luyang Kong
GPFedRec: Graph-Guided Personalization for Federated Recommendation
Chunxu Zhang, Guodong Long, Tianyi Zhou, Zijian Zhang, Peng Yan, Bo Yang
GEO: Generative Engine Optimization
Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Vijayakumar, Karthik Narasimhan, Ameet Deshpande
GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models
Yi Fang, Dongzhe Fan, Daochen Zha, Qiaoyu Tan
Future Impact Decomposition in Request-level Recommendations
Xiaobei Wang, Shuchang Liu, Xueliang Wang, Qingpeng Cai, Lantao Hu, Han Li, Peng Jiang, Kun Gai, Guangming Xie
FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting
Ziqing Ma, Wenwei WANG, Tian Zhou, Chao Chen, Bingqing Peng, Liang Sun, Rong Jin
From Variability to Stability: Advancing RecSys Benchmarking Practices
Valeriy Shevchenko, Nikita Belousov, Alexey Vasilev, Vladimir Zholobov, Artyom Sosedka, Natalia Semenova, Anna Volodkevich, Andrey Savchenko, Alexey Zaytsev
From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language Models
Xumeng Wen, Han Zhang, Shun Zheng, Wei Xu, Jiang Bian
Fredformer: Frequency Debiased Transformer for Time Series Forecasting
Xihao Piao, Zheng Chen, Taichi Murayama, Yasuko Matsubara, Yasushi Sakurai
FreQuant: A Reinforcement-Learning based Adaptive Portfolio Optimization with Multi-frequency Decomposition
Jihyeong Jeon, Jiwon Park, Chanhee Park, U Kang
FoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answering
Tianchi Cai, Zhiwen Tan, Xierui Song, Tao Sun, Jiyan Jiang, Yunqi Xu, Yinger Zhang, Jinjie Gu
Flexible Graph Neural Diffusion with Latent Class Representation Learning
Liangtian Wan, Huijin Han, Lu Sun, Zixun Zhang, Zhaolong Ning, Xiaoran Yan, Feng Xia
FlexCare: Leveraging Cross-Task Synergy for Flexible Multimodal Healthcare Prediction
Muhao Xu, Zhenfeng Zhu, Youru Li, Shuai Zheng, Yawei Zhao, Kunlun He, Yao Zhao
FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning
Weirui Kuang, Bingchen Qian, Zitao Li, Daoyuan Chen, Dawei Gao, Xuchen Pan, Yuexiang Xie, Yaliang Li, Bolin Ding, Jingren Zhou
Federated Graph Learning with Structure Proxy Alignment
Xingbo Fu, Zihan Chen, Binchi Zhang, Chen Chen, Jundong Li
FedSecurity: A Benchmark for Attacks and Defenses in Federated Learning and Federated LLMs
Shanshan Han, Baturalp Buyukates, Zijian Hu, Han Jin, Weizhao Jin, Lichao Sun, Xiaoyang Wang, WENXUAN WU, Chulin Xie, Yuhang Yao, Kai Zhang, Qifan Zhang, Yuhui Zhang, Carlee Joe-Wong, Salman Avestimehr, Chaoyang He
FedSAC: Dynamic Submodel Allocation for Collaborative Fairness in Federated Learning
Zihui Wang, Zheng Wang, Lingjuan Lyu, Zhaopeng Peng, Zhicheng YANG, Chenglu Wen, Rongshan Yu, Cheng Wang, Xiaoliang Fan
FedRoLA: Robust Federated Learning Against Model Poisoning via Layer-based Aggregation
Gang Yan, Hao Wang, Xu Yuan, Jian Li