Sequential Recommendation
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Benchmarks
MovieLens 1M
Amazon-Beauty
Amazon-Sports
Amazon Beauty
Amazon Cell Phones
Amazon Men
Amazon-Toys
Amazon-Video-Games
Behance
Gowalla
KuaiRand
LastFM
Yelp
Most implemented
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
Self-Attentive Sequential Recommendation
TiSASRec: Time Interval Aware Self-Attention for Sequential Recommendation
Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
OpenP5: An Open-Source Platform for Developing, Training, and Evaluating LLM-based Recommender Systems
DeepRec: An Open-source Toolkit for Deep Learning based Recommendation
Papers
IntBMoE: Integrating Block-Level Conditioning into Expert Composition for Full-Participation Mixture-of-Experts
Mixture-of-Experts (MoE) scales capacity, but existing designs cannot set three quantities independently. For a single token, participation is how many experts contribute knowledge to its output, execution is how many ar…
Sequential RecommendationImage ClassificationCRAMER: Control via Request-Aware Masking for Editing Recommenders
Sequential recommendation models, while powerful, have limited flexibility in responding to immediate user requests, making it difficult to adapt their recommendations to the user's timely interests. Unfortunately, exist…
Sequential RecommendationPrompt EngineeringAdapting Knowledge Graphs for Behavior Denoising in Sequential Recommendation
Sequential recommendation predicts the next item from a user's interaction history, but not every interaction is equally informative. Real logs combine persistent preferences with temporary needs, exploration, and incide…
Sequential RecommendationKnowledge GraphsRecPFN: Prior-Fitted Networks for In-Context-Based Recommendations
We introduce RecPFN, a prior-fitted network that brings in-context learning to sequential recommendation. RecPFN is pretrained entirely on synthetic clickstream environments sampled from a broad structural causal prior, …
Sequential RecommendationWhen Machines Speak: A Unified Generative Framework for Integrating Machine-Native Symbols into Pretrained Large Language Models
Many real-world AI systems represent entities, behaviors, and structured information using discrete machine-native symbols rather than natural language. While these representations are compact and preserve task-relevant …
Sequential RecommendationStructured PredictionGOD: Enhancing Generalization via Deep Grafting for Sequential Recommendation
Sequential recommenders often struggle with sparse and noisy histories, limiting generalization to unseen interactions. Knowledge distillation mitigates this by transferring dense supervision from a teacher to a student.…
Sequential RecommendationKnowledge Distillation