Image de couverture de livre

Differentiable Fast Top-K Selection for Large-Scale Recommendation

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhu, Yanjie, Zhang, Zhen, Wang, Yunli, Wang, Zhiqiang, Li, Yu, Zhou, Rufan, Wen, Shiyang, Jiang, Peng, Lin, Chenhao, Yang, Jian
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Scaling Laws for Online Advertisement Retrieval
par: Wang, Yunli, et autres
Publié: (2024)

Learning Cascade Ranking as One Network
par: Wang, Yunli, et autres
Publié: (2025)

Adaptive$^2$: Adaptive Domain Mining for Fine-grained Domain Adaptation Modeling
par: Sun, Wenxuan, et autres
Publié: (2024)

Adaptive Neural Ranking Framework: Toward Maximized Business Goal for Cascade Ranking Systems
par: Wang, Yunli, et autres
Publié: (2023)

Generative Recommendation for Large-Scale Advertising
par: Xue, Ben, et autres
Publié: (2026)

Talos: Optimizing Top-$K$ Accuracy in Recommender Systems
par: Zhang, Shengjia, et autres
Publié: (2026)

Breaking the Top-$K$ Barrier: Advancing Top-$K$ Ranking Metrics Optimization in Recommender Systems
par: Yang, Weiqin, et autres
Publié: (2025)

TopKGAT: A Top-K Objective-Driven Architecture for Recommendation
par: Chen, Sirui, et autres
Publié: (2026)

Top-Personalized-K Recommendation
par: Kweon, Wonbin, et autres
Publié: (2024)

RTop-K: Ultra-Fast Row-Wise Top-K Selection for Neural Network Acceleration on GPUs
par: Xie, Xi, et autres
Publié: (2024)

Top‐Down Central Inspection and Subnational Discretion in Policymaking
par: Shiyang Xiao, et autres
Publié: (2025)

Autoregressive Generation Strategies for Top-K Sequential Recommendations
par: Volodkevich, Anna, et autres
Publié: (2024)

Large-Scale Multi-Domain Recommendation: an Automatic Domain Feature Extraction and Personalized Integration Framework
par: Xi, Dongbo, et autres
Publié: (2024)

RadiK: Scalable and Optimized GPU-Parallel Radix Top-K Selection
par: Li, Yifei, et autres
Publié: (2025)

Recommending Variable Names for Extract Local Variable Refactorings
par: Wang, Taiming, et autres
Publié: (2025)

Beyond One-Size-Fits-All: Personalized Harmful Content Detection with In-Context Learning
par: Zhang, Rufan, et autres
Publié: (2025)

A Traffic Adapative Physics-informed Learning Control for Energy Savings of Connected and Automated Vehicles
par: Shao, Yunli
Publié: (2024)

Optimizing Novelty of Top-k Recommendations using Large Language Models and Reinforcement Learning
par: Sharma, Amit, et autres
Publié: (2024)

An All-Reduce Compatible Top-K Compressor for Communication-Efficient Distributed Learning
par: Chen, Chuyan, et autres
Publié: (2025)

FuXi-β: Towards a Lightweight and Fast Large-Scale Generative Recommendation Model
par: Ye, Yufei, et autres
Publié: (2025)

Spacetime-GR: A Spacetime-Aware Generative Model for Large Scale Online POI Recommendation
par: Lin, Haitao, et autres
Publié: (2025)

Learning to Rank with Top-$K$ Fairness
par: Zhang, Boyang, et autres
Publié: (2025)

Genetic Differentiation and Selection Signatures Revealed by Two Successive Genomic Selection of Large Yellow Croaker Against Parasite .
par: Zhao, Ji, et autres
Publié: (2025)

Simpler is More: Efficient Top-K Nearest Neighbors Search on Large Road Networks
par: Wang, Yiqi, et autres
Publié: (2024)

Reflective Unit Test Generation for Precise Type Error Detection with Large Language Models
par: Yang, Chen, et autres
Publié: (2025)

Shiva-DiT: Residual-Based Differentiable Top-$k$ Selection for Efficient Diffusion Transformers
par: Zhang, Jiaji, et autres
Publié: (2026)

Fig. 3. Marphysa hongkongensa n in Psammoecus delicatus Grouvelle 1908
par: Wang, Zhi, et autres
Publié: (2018)

From Top-1 to Top-K: A Reproducibility Study and Benchmarking of Counterfactual Explanations for Recommender Systems
par: Nguyen, Quang-Huy, et autres
Publié: (2026)

G-Meta: Distributed Meta Learning in GPU Clusters for Large-Scale Recommender Systems
par: Xiao, Youshao, et autres
Publié: (2024)

λScale: Enabling Fast Scaling for Serverless Large Language Model Inference
par: Yu, Minchen, et autres
Publié: (2025)

SoK: Understanding Vulnerabilities in the Large Language Model Supply Chain
par: Wang, Shenao, et autres
Publié: (2025)

Evaluation of Surface Treatment on the Fracture Performance of CFRP / TC4 Adhesively Bonded Joints: Effect of Physical Methods
par: Jian Wang, et autres
Publié: (2026)

RankMixer: Scaling Up Ranking Models in Industrial Recommenders
par: Zhu, Jie, et autres
Publié: (2025)

A Fast Solver-Free Algorithm for Traffic Engineering in Large-Scale Data Center Network
par: Mao, Yingming, et autres
Publié: (2025)

Large Language Model as Universal Retriever in Industrial-Scale Recommender System
par: Jiang, Junguang, et autres
Publié: (2025)

Make It Long, Keep It Fast: End-to-End 10K Long User Behavior Sequence Modeling for Billion-Scale Douyin Recommendation
par: Guan, Lin, et autres
Publié: (2025)

TopKD: Top-scaled Knowledge Distillation
par: Wang, Qi, et autres
Publié: (2025)

TokenMixer-Large: Scaling Up Large Ranking Models in Industrial Recommenders
par: Jiang, Yuchen, et autres
Publié: (2026)

Efficient Retrieval Scaling with Hierarchical Indexing for Large Scale Recommendation
par: Fu, Dongqi, et autres
Publié: (2026)

Fast and Scalable Analytical Diffusion
par: Shang, Xinyi, et autres
Publié: (2026)