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A Reusable Model-agnostic Framework for Faithfully Explainable Recommendation and System Scrutability
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-0-387-85820-3_1openalex-snapshot
Introduction to Recommender Systems Handbook
inferredcites →https://doi.org/10.1007/978-1-4899-7637-6_10openalex-snapshot
Explaining Recommendations: Design and Evaluation
inferredcites →https://doi.org/10.1007/978-3-540-75390-2_4openalex-snapshot
Rule Extraction from Linear Support Vector Machines via Mathematical Programming
inferredcites →https://doi.org/10.1007/s11257-008-9051-3openalex-snapshot
The effects of transparency on trust in and acceptance of a content-based art recommender
inferredcites →https://doi.org/10.1007/s11257-017-9195-0openalex-snapshot
A systematic review and taxonomy of explanations in decision support and recommender systems
inferredcites →https://doi.org/10.1007/s11263-021-01453-zopenalex-snapshot
Knowledge Distillation: A Survey
inferredcites →https://doi.org/10.1016/j.ijhcs.2013.12.007openalex-snapshot
How should I explain? A comparison of different explanation types for recommender systems
inferredcites →https://doi.org/10.1016/s0049-237x(09)x7008-4openalex-snapshot
Harvey Friedman's Research on the Foundations of Mathematics
inferredcites →https://doi.org/10.1023/a:1021240730564openalex-snapshot
Hybrid Recommender Systems: Survey and Experiments
inferredcites →https://doi.org/10.1093/biomet/30.1-2.81openalex-snapshot
A NEW MEASURE OF RANK CORRELATION
inferredcites →https://doi.org/10.1109/34.232078openalex-snapshot
Computation of normalized edit distance and applications
inferredcites →https://doi.org/10.1109/dsaa.2018.00018openalex-snapshot
Explaining Explanations: An Overview of Interpretability of Machine Learning
inferredcites →https://doi.org/10.1109/icdew.2007.4401070openalex-snapshot
A Survey of Explanations in Recommender Systems
inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot
Matrix Factorization Techniques for Recommender Systems
inferredcites →https://doi.org/10.1109/tkde.2022.3221847openalex-snapshot
Aspect-guided Syntax Graph Learning for Explainable Recommendation
inferredcites →https://doi.org/10.1109/tpami.2007.1078openalex-snapshot
A Normalized Levenshtein Distance Metric
inferredcites →https://doi.org/10.1145/1639714.1639768openalex-snapshot
Generating transparent, steerable recommendations from textual descriptions of items
inferredcites →https://doi.org/10.1145/2507157.2507163openalex-snapshot
Hidden factors and hidden topics
inferredcites →https://doi.org/10.1145/2600428.2609579openalex-snapshot
Explicit factor models for explainable recommendation based on phrase-level sentiment analysis
inferredcites →https://doi.org/10.1145/3178876.3186070openalex-snapshot
Neural Attentional Rating Regression with Review-level Explanations
inferredcites →https://doi.org/10.1145/3209978.3210010openalex-snapshot
Explainable Recommendation via Multi-Task Learning in Opinionated Text Data
inferredcites →https://doi.org/10.1145/3297280.3297443openalex-snapshot
Towards explaining recommendations through local surrogate models
inferredcites →https://doi.org/10.1145/3306618.3314229openalex-snapshot
Faithful and Customizable Explanations of Black Box Models
inferredcites →https://doi.org/10.1145/3331184.3331203openalex-snapshot
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation
inferredcites →https://doi.org/10.1145/3331184.3331211openalex-snapshot
Transparent, Scrutable and Explainable User Models for Personalized Recommendation
inferredcites →https://doi.org/10.1145/3336191.3371790openalex-snapshot
Distilling Structured Knowledge into Embeddings for Explainable and Accurate Recommendation
inferredcites →https://doi.org/10.1145/3340531.3411992openalex-snapshot
Generate Neural Template Explanations for Recommendation
inferredcites →https://doi.org/10.1145/3340531.3411993openalex-snapshot
E-commerce Recommendation with Weighted Expected Utility
inferredcites →https://doi.org/10.1145/3351095.3375234openalex-snapshot
Model agnostic interpretability of rankers via intent modelling
inferredcites →https://doi.org/10.1145/3359786openalex-snapshot
Techniques for interpretable machine learning
inferredcites →https://doi.org/10.1145/336992.337035openalex-snapshot
Recommender systems in e-commerce
inferredcites →https://doi.org/10.1145/3397271.3401032openalex-snapshot
Measuring Recommendation Explanation Quality
inferredcites →https://doi.org/10.1145/3397271.3401083openalex-snapshot
A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data
inferredcites →https://doi.org/10.1145/3439729openalex-snapshot
A Survey on Adversarial Recommender Systems
inferredcites →https://doi.org/10.1145/3442381.3449848openalex-snapshot
ELIXIR: Learning from User Feedback on Explanations to Improve Recommender Models
inferredcites →https://doi.org/10.1145/3447548.3467101openalex-snapshot
Embedding-based Product Retrieval in Taobao Search
inferredcites →https://doi.org/10.1145/3450613.3456846openalex-snapshot
Model-Agnostic Counterfactual Explanations of Recommendations
inferredcites →https://doi.org/10.1145/3459637.3482420openalex-snapshot
Counterfactual Explainable Recommendation
inferredcites →https://doi.org/10.1145/3460231.3474273openalex-snapshot
Negative Interactions for Improved Collaborative Filtering: Don’t go Deeper, go Higher
inferredcites →https://doi.org/10.1145/3485447.3511937openalex-snapshot
Path Language Modeling over Knowledge Graphsfor Explainable Recommendation
inferredcites →https://doi.org/10.1145/3506804openalex-snapshot
Counterfactual Explanations for Neural Recommenders
inferredcites →https://doi.org/10.1145/3523227.3547374openalex-snapshot
Hands on Explainable Recommender Systems with Knowledge Graphs
inferredcites →https://doi.org/10.1214/aoms/1177729586openalex-snapshot
A Stochastic Approximation Method
inferredcites →https://doi.org/10.1609/aaai.v32i1.11491openalex-snapshot
Anchors: High-Precision Model-Agnostic Explanations
inferredcites →https://doi.org/10.1609/aaai.v33i01.33015329openalex-snapshot
Explainable Reasoning over Knowledge Graphs for Recommendation
inferredcites →https://doi.org/10.18653/v1/2020.acl-main.386openalex-snapshot
Towards Faithfully Interpretable NLP Systems: How Should We Define and Evaluate Faithfulness?
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-mainopenalex-snapshot
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-main.263openalex-snapshot
A Diagnostic Study of Explainability Techniques for Text Classification
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.253openalex-snapshot
Natural Language Rationales with Full-Stack Visual Reasoning: From Pixels to Semantic Frames to Commonsense Graphs
inferredcites →https://doi.org/10.18653/v1/2021.findings-acl.336openalex-snapshot
Explaining NLP Models via Minimal Contrastive Editing (MiCE)
inferredcites →https://doi.org/10.18653/v1/2021.naacl-main.245openalex-snapshot
Faithfully Explainable Recommendation via Neural Logic Reasoning
inferredcites →https://doi.org/10.18653/v1/d19-1002openalex-snapshot
Attention is not not Explanation
inferredcites →https://doi.org/10.3390/a11090137openalex-snapshot
Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-63797-1_1openalex-snapshot
Model-Agnostic Knowledge Graph Embedding Explanations for Recommender Systems
inferred← citeshttps://doi.org/10.1007/s10994-024-06646-4openalex-snapshot
Reinforced logical reasoning over KGs for interpretable recommendation system
inferred← citeshttps://doi.org/10.1016/j.neunet.2024.106675openalex-snapshot
Knowledge-reinforced explainable next basket recommendation
inferred← citeshttps://doi.org/10.1109/tcss.2025.3603087openalex-snapshot
Enhancing Explainable Sequential Recommendation With Disentangled Representations and Auxiliary Review Explanations
inferred← citeshttps://doi.org/10.1145/3627673.3679804openalex-snapshot
Interaction-level Membership Inference Attack against Recommender Systems with Long-tailed Distribution
inferred← citeshttps://doi.org/10.1145/3640457.3688075openalex-snapshot
Large Language Models as Evaluators for Recommendation Explanations
inferred← citeshttps://doi.org/10.1145/3654806openalex-snapshot
UISA: User Information Separating Architecture for Commodity Recommendation Policy with Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1145/3664190.3672508openalex-snapshot
CFE2: Counterfactual Editing for Search Result Explanation
inferred← citeshttps://doi.org/10.1145/3711856openalex-snapshot
Domain Counterfactual Data Augmentation for Explainable Recommendation
inferred← citeshttps://doi.org/10.1145/3729224openalex-snapshot
CaGE: A Causality-inspired Graph Neural Network Explainer for Recommender Systems
inferred← citeshttps://doi.org/10.1145/3779420openalex-snapshot
Can Offline Metrics Measure Explanation Goals? A Comparative Survey Analysis of Offline Explanation Metrics in Recommender Systems
inferred← citeshttps://doi.org/10.1145/3795529openalex-snapshot
Understanding Internal Representations of Recommendation Models with Sparse Autoencoders
inferred← citeshttps://doi.org/10.1609/aaai.v38i17.29875openalex-snapshot
Graph Neural Prompting with Large Language Models
inferred← citeshttps://doi.org/10.5753/jis.2025.5563openalex-snapshot
Do Calibrated Recommendations Affect Explanations? A Study on Post-Hoc Adjustments
inferred← citeshttps://doi.org/10.5753/webmedia.2024.241857openalex-snapshot
O Impacto de Estratégias de Embeddings de Grafos na Explicabilidade de Sistemas de Recomendação
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