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20242026
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cs.IR2026

Dual-Tree LLM-Enhanced Negative Sampling for Implicit Collaborative Filtering

Jiayi Wu, Zhengyu Wu, Xunkai Li +2

Negative sampling is a pivotal technique in implicit collaborative filtering (CF) recommendation, enabling efficient and effective training by contrasting observed interactions wit…

cs.IR2026

TFPS: A Temporal Filtration-enhanced Positive Sample Set Construction Method for Implicit Collaborative Filtering

Jiayi Wu, Zhengyu Wu, Xunkai Li +2

The negative sampling strategy can effectively train collaborative filtering (CF) recommendation models based on implicit feedback by constructing positive and negative samples. Ho…

cs.IR2026

A Topology-Aware Positive Sample Set Construction and Feature Optimization Method in Implicit Collaborative Filtering

Jiayi Wu, Zhengyu Wu, Xunkai Li +2

Negative sampling strategies are widely used in implicit collaborative filtering to address issues like data sparsity and class imbalance. However, these methods often introduce fa…

cs.IR2026

A Simple yet Effective Negative Sampling Plugin for Constructing Positive Sample Pairs in Implicit Collaborative Filtering

Jiayi Wu, Zhengyu Wu, Xunkai Li +2

Most implicit collaborative filtering (CF) models are trained with negative sampling, where existing work designs sophisticated strategies for high-quality negatives while largely…

cs.IR2025

δ-EMG: A Monotonic Graph Index for Approximate Nearest Neighbor Search

Liming Xiang, Jing Feng, Ziqi Yin +5

Approximate nearest neighbor (ANN) search in high-dimensional spaces is a foundational component of many modern retrieval and recommendation systems. Currently, almost all algorith…