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Mitigating Propensity Bias of Large Language Models for Recommender Systems
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Knowledge Graphs: Opportunities and Challenges
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Spatial-temporal clustering enhanced multi-graph convolutional network for traffic flow prediction
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FPGNN: Fair path graph neural network for mitigating discrimination
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Sound and complete causal identification with latent variables given local background knowledge
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Learning fair representations via rebalancing graph structure
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Graph augmentation for node-level few-shot learning
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Efficient kNN classification algorithm for big data
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Hyper-class representation of data
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Disentangled contrastive learning for fair graph representations
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Causal Inference for Statistics, Social, and Biomedical Sciences
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Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation
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Spatial–Spectral Graph Contrastive Clustering With Hard Sample Mining for Hyperspectral Images
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Challenges in KNN Classification
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KNN Classification with One-step Computation
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A Multi-View Multi-Task Learning Framework for Multi-Variate Time Series Forecasting
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Causal Inference for Knowledge Graph Based Recommendation
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Enhanced Multi-Task Learning and Knowledge Graph-Based Recommender System
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XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation
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Learning Graph ODE for Continuous-Time Sequential Recommendation
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Neural Graph Collaborative Filtering
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Self-supervised Graph Learning for Recommendation
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Persistent Anti-Muslim Bias in Large Language Models
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Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Causal Mediation Analysis with Hidden Confounders
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A Survey of Machine Learning for Computer Architecture and Systems
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Federated Social Recommendation with Graph Neural Network
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Knowledge-Enhanced Attributed Multi-Task Learning for Medicine Recommendation
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Towards Representation Alignment and Uniformity in Collaborative Filtering
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Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited
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FASTER: A Dynamic Fairness-assurance Strategy for Session-based Recommender Systems
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Representation Learning with Large Language Models for Recommendation
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TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation
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LLMRec: Large Language Models with Graph Augmentation for Recommendation
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On Generative Agents in Recommendation
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Large Language Models Portray Socially Subordinate Groups as More Homogeneous, Consistent with a Bias Observed in Humans
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Data-Driven Causal Effect Estimation Based on Graphical Causal Modelling: A Survey
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A Review of Graph Neural Networks in Epidemic Modeling
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Miko: Multimodal Intention Knowledge Distillation from Large Language Models for Social-Media Commonsense Discovery
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Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach
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Graph Structure Learning with Variational Information Bottleneck
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Disentangled Representation for Causal Mediation Analysis
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Distribution-Conditioned Adversarial Variational Autoencoder for Valid Instrumental Variable Generation
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Gender and Representation Bias in GPT-3 Generated Stories
inferredcites →https://doi.org/10.18653/v1/2023.emnlp-main.621openalex-snapshot
Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models
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CoMPosT: Characterizing and Evaluating Caricature in LLM Simulations
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Aligning Large Language Models for Controllable Recommendations
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Text-like Encoding of Collaborative Information in Large Language Models for Recommendation
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Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods
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Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias
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FASTER: A Dynamic Fairness-assurance Strategy for Session-based Recommender Systems
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/widm.70020openalex-snapshot
A Survey on Causal Inference‐Driven Data Bias Optimization in Recommendation Systems: Principles, Opportunities and Challenges
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The quasi-gods of algorithmic providence: recommender systems and religious frameworks
inferred← citeshttps://doi.org/10.1007/s10115-026-02737-xopenalex-snapshot
RichGNN: Attribute-enriched graph neural network for optimized e-commerce recommendations
inferred← citeshttps://doi.org/10.1007/s42452-025-07551-8openalex-snapshot
Learning to represent causality in recommender systems driven by large language models (LLMs)
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.128726openalex-snapshot
Consistent focus: Mitigating permutation bias in large language models through attention weight averaging
inferred← citeshttps://doi.org/10.1016/j.ipm.2025.104268openalex-snapshot
A pseudo-labeling approach based on knowledge distillation for graph few-shot learning
inferred← citeshttps://doi.org/10.1016/j.ipm.2025.104395openalex-snapshot
Over-smoothing problem of heterogeneous graph neural networks: A heterogeneous graph neural network with enhanced node differentiability
inferred← citeshttps://doi.org/10.1016/j.ipm.2026.104933openalex-snapshot
Causal deconfounding via multiplex spatial–temporal confounder disentanglement for next POI recommendation
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.114345openalex-snapshot
Multi-Cause Deconfounding for Recommender Systems with Latent Confounders
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.114470openalex-snapshot
MRBalance: A framework for enhancing event causality identification in multi-agent debates via role assignment
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.114583openalex-snapshot
Incomplete graph learning via data and representation-level interaction
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.131330openalex-snapshot
Certainty-aware support vector machines for fair classification
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.131787openalex-snapshot
Feature representation learning for image denoising
inferred← citeshttps://doi.org/10.1109/jstars.2026.3725794openalex-snapshot
Self-Contrastive Graph Diffusion Clustering for Hyperspectral Images
inferred← citeshttps://doi.org/10.1109/swc65939.2025.00120openalex-snapshot
Mitigating Item-Side Unfairness in LLM-Enhanced Recommender Systems
inferred← citeshttps://doi.org/10.1109/tbdata.2025.3624955openalex-snapshot
NTFormer: A Composite Node Tokenized Graph Transformer for Node Classification
inferred← citeshttps://doi.org/10.1109/tcss.2025.3577900openalex-snapshot
Multibehavior Intent Disentangled Learning for Fine-Grained Interest Discovery in Recommendation
inferred← citeshttps://doi.org/10.1109/tcss.2026.3661211openalex-snapshot
Causal Prompting for Implicit Sentiment Analysis With Large Language Models
inferred← citeshttps://doi.org/10.1109/tcss.2026.3708165openalex-snapshot
SDADL: SVD-Based Dual Adaptive Debiasing Learning for Personalized Recommendation
inferred← citeshttps://doi.org/10.1109/tgrs.2026.3669248openalex-snapshot
Graph Contrastive Learning With High-Order Relations for Hyperspectral Image Clustering
inferred← citeshttps://doi.org/10.1109/tim.2025.3588988openalex-snapshot
Enhancing Multimodal Action Recognition With Semantic-Guided Feature Disentangled and Multichannel Adaptive Feature Fusion
inferred← citeshttps://doi.org/10.1109/tmech.2026.3716307openalex-snapshot
Rising From Embodied Intelligence to Embedded Intelligence via Decentralized Federated Learning With Roaming AI Agents
inferred← citeshttps://doi.org/10.1145/3746252.3761177openalex-snapshot
Mitigating Latent Confounding Bias in Recommender Systems
inferred← citeshttps://doi.org/10.1145/3747838openalex-snapshot
Introduction to the Special Issue on Causality Representation Learning in LLMs-Driven Recommender Systems
inferred← citeshttps://doi.org/10.1145/3770854.3780335openalex-snapshot
Mitigating Privacy Risks in Graph Condensation from a Hyperbolic Geometry Perspective
inferred← citeshttps://doi.org/10.1145/3785503openalex-snapshot
Towards Fair Graph Representation Learning by Overcoming Social Homophily
inferred← citeshttps://doi.org/10.1145/3800942openalex-snapshot
Matryoshka Representation Learning for Recommendation with Layer- and Hardness-Adaptive Negative Sampling
inferred← citeshttps://doi.org/10.21203/rs.3.rs-10007904/v1openalex-snapshot
Enhancing Cognitive Diagnosis with Group-Aware Graph Augmentation and Self-Supervised Alignment
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