Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model | Paper Citation Record

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This paper cites Recurrent neural networks with top-k gains for session-based recommendations.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Recurrent neural networks with top-k gains for session-based recommendations

Reference 1

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This paper cites Parallel recurrent neural network architectures for feature-rich session-based recommendations.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Parallel recurrent neural network architectures for feature-rich session-based recommendations

Reference 2

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This paper cites Personalizing session-based recommendations with hierarchical recurrent neural networks.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Personalizing session-based recommendations with hierarchical recurrent neural networks

Reference 3

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This paper cites Self-attentive sequential recommendation.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Self-attentive sequential recommendation

Reference 4

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This paper cites Bert4rec: Sequential recommen- dation with bidirectional encoder representations from transformer.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Bert4rec: Sequential recommen- dation with bidirectional encoder representations from transformer

Reference 5

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This paper cites Personalized top-n sequential recommendation via convolutional sequence embedding.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Personalized top-n sequential recommendation via convolutional sequence embedding

Reference 6

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This paper cites A simple convolutional generative network for next item recommendation.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model A simple convolutional generative network for next item recommendation

Reference 7

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This paper cites Session-based recommendation with graph neural networks.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Session-based recommendation with graph neural networks

Reference 8

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This paper cites Memory augmented graph neural networks for sequential recommendation.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Memory augmented graph neural networks for sequential recommendation

Reference 9

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This paper cites Modeling sequences as distributions with uncertainty for sequential recommendation.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Modeling sequences as distributions with uncertainty for sequential recommendation

Reference 10

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This paper cites Solving the apparent diversity-accuracy dilemma of recommender systems.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Solving the apparent diversity-accuracy dilemma of recommender systems

Reference 11

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This paper cites Denoising diffusion probabilistic models.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Denoising diffusion probabilistic models

Reference 12

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This paper cites Diffurec: A diffusion model for sequential recommendation.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Diffurec: A diffusion model for sequential recommendation

Reference 13

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This paper cites An mdp-based recommender system.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model An mdp-based recommender system

Reference 14

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This paper cites Factorizing personalized markov chains for next-basket recommendation.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Factorizing personalized markov chains for next-basket recommendation

Reference 15

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This paper cites Translation-based recommendation.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Translation-based recommendation

Reference 16

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This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 17

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This paper cites Long short-term memory.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Long short-term memory

Reference 18

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This paper cites Attention is all you need.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Attention is all you need

Reference 19

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This paper cites Auto-Encoding Variational Bayes.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Auto-Encoding Variational Bayes

Reference 20

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This paper cites Generative adversarial networks.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Generative adversarial networks

Reference 21

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This paper cites Mvae: Multimodal variational autoen- coder for fake news detection.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Mvae: Multimodal variational autoen- coder for fake news detection

Reference 22

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This paper cites Adversarial and contrastive variational autoencoder for sequential recommendation.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Adversarial and contrastive variational autoencoder for sequential recommendation

Reference 23

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This paper cites Recgan: recurrent generative adversarial networks for recommendation systems.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Recgan: recurrent generative adversarial networks for recommendation systems

Reference 24

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This paper cites Sequential recommendation with self-attentive multi-adversarial network.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Sequential recommendation with self-attentive multi-adversarial network

Reference 25

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This paper cites Understanding posterior collapse in generative latent variable models.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Understanding posterior collapse in generative latent variable models

Reference 26

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This paper cites Infovae: Balancing learning and inference in variational autoencoders.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Infovae: Balancing learning and inference in variational autoencoders

Reference 27

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This paper cites Improved techniques for training gans.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Improved techniques for training gans

Reference 28

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This paper cites Improved variational inference with inverse autoregressive flow.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Improved variational inference with inverse autoregressive flow

Reference 29

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This paper cites Diffusion recommender model.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Diffusion recommender model

Reference 30

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This paper cites Discrete Conditional Diffusion for Reranking in Recommendation.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Discrete Conditional Diffusion for Reranking in Recommendation

Reference 31

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This paper cites Diffusion augmentation for sequential recommendation.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Diffusion augmentation for sequential recommendation

Reference 32

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This paper cites Fairness in recommendation: Foundations, methods, and applications.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Fairness in recommendation: Foundations, methods, and applications

Reference 33

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Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model User-oriented fairness in recommen- dation

Reference 34

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This paper cites Beyond parity: Fairness objectives for collaborative filtering.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Beyond parity: Fairness objectives for collaborative filtering

Reference 35

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This paper cites Privacy-aware recommendation with private-attribute protection using adversarial learning.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Privacy-aware recommendation with private-attribute protection using adversarial learning

Reference 36

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Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Fairness-aware news recommendation with decomposed adversarial learning

Reference 37

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This paper cites Toward pareto efficient fairness-utility trade-off in recommendation through reinforcement learning.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Toward pareto efficient fairness-utility trade-off in recommendation through reinforcement learning

Reference 38

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Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Balancing Accuracy and Fairness for Interactive Recommendation with Reinforcement Learning

Reference 39

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This paper cites On discrimination discovery and removal in ranked data using causal graph.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model On discrimination discovery and removal in ranked data using causal graph

Reference 40

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This paper cites Disentangling user interest and conformity for recommendation with causal embedding.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Disentangling user interest and conformity for recommendation with causal embedding

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This paper cites U-net: Convolutional networks for biomedical image segmentation.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model U-net: Convolutional networks for biomedical image segmentation

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This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Deep unsupervised learning using nonequilibrium thermodynamics

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Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Dynamic routing between capsules

Reference 44

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This paper cites Multi-interest network with dynamic routing for recommendation at tmall.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Multi-interest network with dynamic routing for recommendation at tmall

Reference 45

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Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Controllable multi-interest framework for recommendation

Reference 46

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Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Personalized transfer of user preferences for cross-domain recommendation

Reference 47

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This paper cites Sequential recommendation via stochastic self-attention.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Sequential recommendation via stochastic self-attention

Reference 48

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This paper cites Selective fairness in recommendation via prompts.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Selective fairness in recommendation via prompts

Reference 49

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This paper cites Diffusion-lm improves controllable text generation.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Diffusion-lm improves controllable text generation

Reference 50

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This paper cites Structured denoising diffusion models in discrete state-spaces.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Structured denoising diffusion models in discrete state-spaces

Reference 51

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This paper cites Improved denoising diffusion probabilistic models.

Alleviating User-Sensitive bias with Fair Generative Sequential Recommendation Model Improved denoising diffusion probabilistic models

Reference 52

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