Hierarchical Structured Neural Network: Efficient Retrieval Scaling for Large Scale Recommendation
Fuente:
arXiv
Saved in:
| Main Authors: | Rangadurai, Kaushik, Yuan, Siyang, Huang, Minhui, Liu, Yiqun, Ghasemiesfeh, Golnaz, Pu, Yunchen, Lu, Haiyu, He, Xingfeng, Xu, Fangzhou, Cui, Andrew, Viswanathan, Vidhoon, Yang, Lin, Wang, Liang, Yang, Jiyan, Sun, Chonglin |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Efficient Retrieval Scaling with Hierarchical Indexing for Large Scale Recommendation
by: Fu, Dongqi, et al.
Published: (2026)
by: Fu, Dongqi, et al.
Published: (2026)
Hierarchical LoRA MoE for Efficient CTR Model Scaling
by: Zeng, Zhichen, et al.
Published: (2025)
by: Zeng, Zhichen, et al.
Published: (2025)
Enhancing Embedding Representation Stability in Recommendation Systems with Semantic ID
by: Zheng, Carolina, et al.
Published: (2025)
by: Zheng, Carolina, et al.
Published: (2025)
Multi-behavior Recommendation with SVD Graph Neural Networks
by: Fu, Shengxi, et al.
Published: (2023)
by: Fu, Shengxi, et al.
Published: (2023)
Beyond Self-Consistency: Loss-Balanced Perturbation-Based Regularization Improves Industrial-Scale Ads Ranking
by: Ramazanli, Ilqar, et al.
Published: (2025)
by: Ramazanli, Ilqar, et al.
Published: (2025)
Scaling Laws For Dense Retrieval
by: Fang, Yan, et al.
Published: (2024)
by: Fang, Yan, et al.
Published: (2024)
Retrieval-Augmented Recommendation Explanation Generation with Hierarchical Aggregation
by: Sun, Bangcheng, et al.
Published: (2025)
by: Sun, Bangcheng, et al.
Published: (2025)
MultiBalance: Multi-Objective Gradient Balancing in Industrial-Scale Multi-Task Recommendation System
by: He, Yun, et al.
Published: (2024)
by: He, Yun, et al.
Published: (2024)
Kunlun: Establishing Scaling Laws for Massive-Scale Recommendation Systems through Unified Architecture Design
by: Hou, Bojian, et al.
Published: (2026)
by: Hou, Bojian, et al.
Published: (2026)
Meta Lattice: Model Space Redesign for Cost-Effective Industry-Scale Ads Recommendations
by: Luo, Liang, et al.
Published: (2025)
by: Luo, Liang, et al.
Published: (2025)
R3-REC: Reasoning-Driven Recommendation via Retrieval-Augmented LLMs over Multi-Granular Interest Signals
by: Miao, Yuchen, et al.
Published: (2026)
by: Miao, Yuchen, et al.
Published: (2026)
Scaling Generative Recommendations with Context Parallelism on Hierarchical Sequential Transducers
by: Dong, Yue, et al.
Published: (2025)
by: Dong, Yue, et al.
Published: (2025)
Measuring Fairness in Large-Scale Recommendation Systems with Missing Labels
by: Dong, Yulong, et al.
Published: (2024)
by: Dong, Yulong, et al.
Published: (2024)
PinRec: Outcome-Conditioned, Multi-Token Generative Retrieval for Industry-Scale Recommendation Systems
by: Agarwal, Prabhat, et al.
Published: (2025)
by: Agarwal, Prabhat, et al.
Published: (2025)
Macro Graph Neural Networks for Online Billion-Scale Recommender Systems
by: Chen, Hao, et al.
Published: (2024)
by: Chen, Hao, et al.
Published: (2024)
Test-Time Scaling Strategies for Generative Retrieval in Multimodal Conversational Recommendations
by: Hsu, Hung-Chun, et al.
Published: (2025)
by: Hsu, Hung-Chun, et al.
Published: (2025)
Large Language Model as Universal Retriever in Industrial-Scale Recommender System
by: Jiang, Junguang, et al.
Published: (2025)
by: Jiang, Junguang, et al.
Published: (2025)
RankMixer: Scaling Up Ranking Models in Industrial Recommenders
by: Zhu, Jie, et al.
Published: (2025)
by: Zhu, Jie, et al.
Published: (2025)
Enhancing LLM-Based Agents via Global Planning and Hierarchical Execution
by: Chen, Junjie, et al.
Published: (2025)
by: Chen, Junjie, et al.
Published: (2025)
ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval
by: Huang, Suyuan, et al.
Published: (2024)
by: Huang, Suyuan, et al.
Published: (2024)
LONGER: Scaling Up Long Sequence Modeling in Industrial Recommenders
by: Chai, Zheng, et al.
Published: (2025)
by: Chai, Zheng, et al.
Published: (2025)
PLAID SHIRTTT for Large-Scale Streaming Dense Retrieval
by: Lawrie, Dawn, et al.
Published: (2024)
by: Lawrie, Dawn, et al.
Published: (2024)
Bending the Scaling Law Curve in Large-Scale Recommendation Systems
by: Ding, Qin, et al.
Published: (2026)
by: Ding, Qin, et al.
Published: (2026)
On the Scaling of Robustness and Effectiveness in Dense Retrieval
by: Liu, Yu-An, et al.
Published: (2025)
by: Liu, Yu-An, et al.
Published: (2025)
Scaling Laws for Online Advertisement Retrieval
by: Wang, Yunli, et al.
Published: (2024)
by: Wang, Yunli, et al.
Published: (2024)
Scaling Recommender Transformers to One Billion Parameters
by: Khrylchenko, Kirill, et al.
Published: (2025)
by: Khrylchenko, Kirill, et al.
Published: (2025)
Masked Graph Transformer for Large-Scale Recommendation
by: Chen, Huiyuan, et al.
Published: (2024)
by: Chen, Huiyuan, et al.
Published: (2024)
Generative Recommendation for Large-Scale Advertising
by: Xue, Ben, et al.
Published: (2026)
by: Xue, Ben, et al.
Published: (2026)
Hi-SAM: A Hierarchical Structure-Aware Multi-modal Framework for Large-Scale Recommendation
by: Pan, Pingjun, et al.
Published: (2026)
by: Pan, Pingjun, et al.
Published: (2026)
TokenMixer-Large: Scaling Up Large Ranking Models in Industrial Recommenders
by: Jiang, Yuchen, et al.
Published: (2026)
by: Jiang, Yuchen, et al.
Published: (2026)
MERGE: Next-Generation Item Indexing Paradigm for Large-Scale Streaming Recommendation
by: Yan, Jing, et al.
Published: (2026)
by: Yan, Jing, et al.
Published: (2026)
Structured Spectral Reasoning for Frequency-Adaptive Multimodal Recommendation
by: Yang, Wei, et al.
Published: (2025)
by: Yang, Wei, et al.
Published: (2025)
Self-supervised Hierarchical Representation for Medication Recommendation
by: Liang, Yuliang, et al.
Published: (2024)
by: Liang, Yuliang, et al.
Published: (2024)
Compress, Cross and Scale: Multi-Level Compression Cross Networks for Efficient Scaling in Recommender Systems
by: Yu, Heng, et al.
Published: (2026)
by: Yu, Heng, et al.
Published: (2026)
Sequential Recommendation with Latent Relations based on Large Language Model
by: Yang, Shenghao, et al.
Published: (2024)
by: Yang, Shenghao, et al.
Published: (2024)
MTGR: Industrial-Scale Generative Recommendation Framework in Meituan
by: Han, Ruidong, et al.
Published: (2025)
by: Han, Ruidong, et al.
Published: (2025)
Towards Generalizable and Efficient Large-Scale Generative Recommenders
by: Xu, Qiuling, et al.
Published: (2026)
by: Xu, Qiuling, et al.
Published: (2026)
Scaling Transformers for Discriminative Recommendation via Generative Pretraining
by: Wang, Chunqi, et al.
Published: (2025)
by: Wang, Chunqi, et al.
Published: (2025)
Stratified Expert Cloning for Retention-Aware Recommendation at Scale
by: Lin, Chengzhi, et al.
Published: (2025)
by: Lin, Chengzhi, et al.
Published: (2025)
Adaptive Domain Scaling for Personalized Sequential Modeling in Recommenders
by: Chai, Zheng, et al.
Published: (2025)
by: Chai, Zheng, et al.
Published: (2025)
Similar Items
-
Efficient Retrieval Scaling with Hierarchical Indexing for Large Scale Recommendation
by: Fu, Dongqi, et al.
Published: (2026) -
Hierarchical LoRA MoE for Efficient CTR Model Scaling
by: Zeng, Zhichen, et al.
Published: (2025) -
Enhancing Embedding Representation Stability in Recommendation Systems with Semantic ID
by: Zheng, Carolina, et al.
Published: (2025) -
Multi-behavior Recommendation with SVD Graph Neural Networks
by: Fu, Shengxi, et al.
Published: (2023) -
Beyond Self-Consistency: Loss-Balanced Perturbation-Based Regularization Improves Industrial-Scale Ads Ranking
by: Ramazanli, Ilqar, et al.
Published: (2025)