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RSS: Effective and Efficient Training for Sequential Recommendation Using Recency Sampling
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-1-0716-2197-4_15openalex-snapshot
Evaluating Recommender Systems
inferredcites →https://doi.org/10.1007/978-1-0716-2197-4_3openalex-snapshot
Advances in Collaborative Filtering
inferredcites →https://doi.org/10.1007/978-3-030-58285-2_23openalex-snapshot
Integrating Keywords into BERT4Rec for Sequential Recommendation
inferredcites →https://doi.org/10.1007/978-3-030-88942-5_24openalex-snapshot
KATRec: Knowledge Aware aTtentive Sequential Recommendations
inferredcites →https://doi.org/10.1007/s10791-021-09397-1openalex-snapshot
Variational Bayesian representation learning for grocery recommendation
inferredcites →https://doi.org/10.1007/s11257-018-9209-6openalex-snapshot
Evaluation of session-based recommendation algorithms
inferredcites →https://doi.org/10.1007/s11704-022-1184-8openalex-snapshot
TransRec++: Translation-based sequential recommendation with heterogeneous feedback
inferredcites →https://doi.org/10.1109/access.2022.3160466openalex-snapshot
ARERec: Attentive Local Interaction Model for Sequential Recommendation
inferredcites →https://doi.org/10.1109/icdm.2018.00035openalex-snapshot
Self-Attentive Sequential Recommendation
inferredcites →https://doi.org/10.1109/icdmw53433.2021.00013openalex-snapshot
CoBERT: Scientific Collaboration Prediction via Sequential Recommendation
inferredcites →https://doi.org/10.1109/tkde.2021.3050571openalex-snapshot
Intention-Aware Sequential Recommendation With Structured Intent Transition
inferredcites →https://doi.org/10.1109/tkde.2022.3151618openalex-snapshot
Dynamic Graph Neural Networks for Sequential Recommendation
inferredcites →https://doi.org/10.1145/1772690.1772773openalex-snapshot
Factorizing personalized Markov chains for next-basket recommendation
inferredcites →https://doi.org/10.1145/3159652.3159656openalex-snapshot
Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
inferredcites →https://doi.org/10.1145/3209978.3210017openalex-snapshot
Improving Sequential Recommendation with Knowledge-Enhanced Memory Networks
inferredcites →https://doi.org/10.1145/3269206.3271761openalex-snapshot
Recurrent Neural Networks with Top-k Gains for Session-based Recommendations
inferredcites →https://doi.org/10.1145/3269206.3271786openalex-snapshot
Representing and Recommending Shopping Baskets with Complementarity, Compatibility and Loyalty
inferredcites →https://doi.org/10.1145/3289600.3290975openalex-snapshot
A Simple Convolutional Generative Network for Next Item Recommendation
inferredcites →https://doi.org/10.1145/3292500.3330984openalex-snapshot
Hierarchical Gating Networks for Sequential Recommendation
inferredcites →https://doi.org/10.1145/3308558.3313447openalex-snapshot
Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm
inferredcites →https://doi.org/10.1145/3340531.3411954openalex-snapshot
S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization
inferredcites →https://doi.org/10.1145/3382764openalex-snapshot
Exploiting Cross-session Information for Session-based Recommendation with Graph Neural Networks
inferredcites →https://doi.org/10.1145/3383313.3412216openalex-snapshot
MEANTIME: Mixture of Attention Mechanisms with Multi-temporal Embeddings for Sequential Recommendation
inferredcites →https://doi.org/10.1145/3383313.3412259openalex-snapshot
On Target Item Sampling in Offline Recommender System Evaluation
inferredcites →https://doi.org/10.1145/3394486.3403091openalex-snapshot
Disentangled Self-Supervision in Sequential Recommenders
inferredcites →https://doi.org/10.1145/3394486.3403226openalex-snapshot
On Sampled Metrics for Item Recommendation
inferredcites →https://doi.org/10.1145/3404835.3462973openalex-snapshot
New Insights into Metric Optimization for Ranking-based Recommendation
inferredcites →https://doi.org/10.1145/3404835.3463036openalex-snapshot
Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer
inferredcites →https://doi.org/10.1145/3404835.3463240openalex-snapshot
Booking.com Multi-Destination Trips Dataset
inferredcites →https://doi.org/10.1145/3459637.3481905openalex-snapshot
Contrastive Curriculum Learning for Sequential User Behavior Modeling via Data Augmentation
inferredcites →https://doi.org/10.1145/3460231.3475943openalex-snapshot
A Case Study on Sampling Strategies for Evaluating Neural Sequential Item Recommendation Models
inferredcites →https://doi.org/10.1145/3473339openalex-snapshot
Exploiting Positional Information for Session-Based Recommendation
inferredcites →https://doi.org/10.1145/3488560.3498433openalex-snapshot
Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation
inferredcites →https://doi.org/10.1145/3522673openalex-snapshot
Sequential Recommendation with Multiple Contrast Signals
inferredcites →https://doi.org/10.1145/3523227.3546785openalex-snapshot
Effective and Efficient Training for Sequential Recommendation using Recency Sampling
inferredcites →https://doi.org/10.1145/3523227.3548487openalex-snapshot
A Systematic Review and Replicability Study of BERT4Rec for Sequential Recommendation
inferredcites →https://doi.org/10.1561/1500000016openalex-snapshot
Learning to Rank for Information Retrieval
inferredcites →https://doi.org/10.48550/arxiv.1910.10683openalex-snapshot
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
inferredcites →https://doi.org/10.48550/arxiv.2108.07505openalex-snapshot
MOI-Mixer: Improving MLP-Mixer with Multi Order Interactions in Sequential Recommendation
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-56069-9_39openalex-snapshot
Effective and Efficient Transformer Models for Sequential Recommendation
inferred← citeshttps://doi.org/10.1016/j.engappai.2024.109366openalex-snapshot
Revisiting the loss functions in sequential recommendation
inferred← citeshttps://doi.org/10.1016/j.ipm.2026.104764openalex-snapshot
KG-LTSR: Knowledge graph-augmented contrastive learning for sequential recommendation of long-tail users
inferred← citeshttps://doi.org/10.1109/icde65448.2025.00089openalex-snapshot
DELRec: Distilling Sequential Pattern to Enhance LLMs-Based Sequential Recommendation
inferred← citeshttps://doi.org/10.1109/iscait69154.2026.11477490openalex-snapshot
A Preference Convergence and Clustering Network for Sequential Recommendation
inferred← citeshttps://doi.org/10.1145/3640457.3688168openalex-snapshot
Efficient Inference of Sub-Item Id-based Sequential Recommendation Models with Millions of Items
inferred← citeshttps://doi.org/10.1145/3650215.3650352openalex-snapshot
Effective and Efficient Training for Sequential Recommendation Using Cumulative Cross-Entropy Loss
inferred← citeshttps://doi.org/10.1145/3699521openalex-snapshot
Improving Effectiveness by Reducing Overconfidence in Large Catalogue Sequential Recommendation with gBCE loss
inferred← citeshttps://doi.org/10.1145/3705328.3748154openalex-snapshot
How Powerful are LLMs to Support Multimodal Recommendation? A Reproducibility Study of LLMRec
inferred← citeshttps://doi.org/10.1145/3705328.3759317openalex-snapshot
eSASRec: Enhancing Transformer-based Recommendations in a Modular Fashion
inferred← citeshttps://doi.org/10.1145/3731458openalex-snapshot
Beyond Recommendations: Sequential Recommendation with Collaborative Explanation
inferred← citeshttps://doi.org/10.1145/3774904.3792124openalex-snapshot
Generative Data Transformation: From Mixed to Unified Data
inferred← citeshttps://doi.org/10.1145/3805712.3809656openalex-snapshot
Filling the Gaps: Selective Knowledge Augmentation for LLM Recommenders
inferred← citeshttps://doi.org/10.1145/3805712.3809738openalex-snapshot
Diagnosing and Mitigating Mid-Sequence Degradation in Recommender Systems
inferred← citeshttps://doi.org/10.1145/3820247openalex-snapshot
Smoothed Intent Learning for Sequential Recommendation
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