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A Troubling Analysis of Reproducibility and Progress in Recommender
  Systems Research
v1v2v3 (latest)

A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research

18 November 2019
Maurizio Ferrari Dacrema
Simone Boglio
Paolo Cremonesi
Dietmar Jannach
ArXiv (abs)PDFHTML

Papers citing "A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research"

50 / 69 papers shown
Title
Building Trustworthy AI for Materials Discovery: From Autonomous Laboratories to Z-scores
Building Trustworthy AI for Materials Discovery: From Autonomous Laboratories to Z-scores
Benhour Amirian
Ashley S. Dale
Sergei Kalinin
Jason Hattrick-Simpers
16
0
0
30 Nov 2025
What Data is Really Necessary? A Feasibility Study of Inference Data Minimization for Recommender Systems
What Data is Really Necessary? A Feasibility Study of Inference Data Minimization for Recommender Systems
Jens Leysen
Marco Favier
Bart Goethals
69
0
0
29 Aug 2025
The Hidden Cost of Defaults in Recommender System Evaluation
The Hidden Cost of Defaults in Recommender System EvaluationACM Conference on Recommender Systems (RecSys), 2025
Hannah Berlin
Robin Svahn
Alan Said
OffRL
68
0
0
28 Aug 2025
A Comparative Study of Recommender Systems under Big Data Constraints
A Comparative Study of Recommender Systems under Big Data Constraints
Arimondo Scrivano
92
0
0
11 Apr 2025
Why is Normalization Necessary for Linear Recommenders?
Why is Normalization Necessary for Linear Recommenders?Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2025
Seongmin Park
Mincheol Yoon
Hye-young Kim
Jongwuk Lee
272
2
0
08 Apr 2025
Reproducibility and Artifact Consistency of the SIGIR 2022 Recommender Systems Papers Based on Message Passing
Maurizio Ferrari Dacrema
Michael Benigni
Nicola Ferro
209
2
0
10 Mar 2025
A Worrying Reproducibility Study of Intent-Aware Recommendation Models
A Worrying Reproducibility Study of Intent-Aware Recommendation ModelsAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2025
Faisal Shehzad
Maurizio Ferrari Dacrema
Dietmar Jannach
126
2
0
20 Jan 2025
Dataset-Agnostic Recommender Systems
Dataset-Agnostic Recommender Systems
Tri Kurniawan Wijaya
Edoardo DÁmico
Xinyang Shao
246
1
0
13 Jan 2025
Fuzzy Norm-Explicit Product Quantization for Recommender Systems
Fuzzy Norm-Explicit Product Quantization for Recommender SystemsIEEE transactions on fuzzy systems (IEEE Trans. Fuzzy Syst.), 2024
Mohammadreza Jamalifard
Javier Andreu-Perez
H. Hagras
Luis Martínez López
361
1
0
08 Dec 2024
Recommender Systems for Good (RS4Good): Survey of Use Cases and a Call to Action for Research that Matters
Recommender Systems for Good (RS4Good): Survey of Use Cases and a Call to Action for Research that MattersACM Transactions on Recommender Systems (TRS), 2024
Dietmar Jannach
Alan Said
Marko Tkalčič
Markus Zanker
222
1
0
25 Nov 2024
Analyzing the Effectiveness of Quantum Annealing with Meta-Learning
Analyzing the Effectiveness of Quantum Annealing with Meta-LearningQuantum Machine Intelligence (QMI), 2024
Guokai Li
Maurizio Ferrari Dacrema
84
3
0
01 Aug 2024
Questionable practices in machine learning
Questionable practices in machine learning
Gavin Leech
Juan J. Vazquez
Misha Yagudin
Niclas Kupper
Laurence Aitchison
228
6
0
17 Jul 2024
An Interpretable Alternative to Neural Representation Learning for
  Rating Prediction -- Transparent Latent Class Modeling of User Reviews
An Interpretable Alternative to Neural Representation Learning for Rating Prediction -- Transparent Latent Class Modeling of User Reviews
Giuseppe Serra
Peter Tino
Zhao Xu
Xin Yao
157
0
0
17 Jun 2024
Position: Why We Must Rethink Empirical Research in Machine Learning
Position: Why We Must Rethink Empirical Research in Machine LearningInternational Conference on Machine Learning (ICML), 2024
Moritz Herrmann
F. J. D. Lange
Katharina Eggensperger
Giuseppe Casalicchio
Marcel Wever
Matthias Feurer
David Rügamer
Eyke Hüllermeier
A. Boulesteix
B. Bischl
228
20
0
03 May 2024
From Variability to Stability: Advancing RecSys Benchmarking Practices
From Variability to Stability: Advancing RecSys Benchmarking Practices
Valeriy Shevchenko
Nikita Belousov
Alexey Vasilev
Vladimir Zholobov
Artyom Sosedka
Natalia Semenova
Anna Volodkevich
Ivan A Kireev
Alexey Zaytsev
144
12
0
15 Feb 2024
Fast Dual-Regularized Autoencoder for Sparse Biological Data
Fast Dual-Regularized Autoencoder for Sparse Biological Data
Aleksandar Poleksic
BDL
130
1
0
30 Jan 2024
Performance Comparison of Session-based Recommendation Algorithms based
  on GNNs
Performance Comparison of Session-based Recommendation Algorithms based on GNNs
Faisal Shehzad
Dietmar Jannach
137
7
0
27 Dec 2023
To Copy, or not to Copy; That is a Critical Issue of the Output Softmax
  Layer in Neural Sequential Recommenders
To Copy, or not to Copy; That is a Critical Issue of the Output Softmax Layer in Neural Sequential RecommendersWeb Search and Data Mining (WSDM), 2023
Haw-Shiuan Chang
Nikhil Agarwal
Andrew McCallum
142
6
0
21 Oct 2023
Evaluating ChatGPT as a Recommender System: A Rigorous Approach
Evaluating ChatGPT as a Recommender System: A Rigorous Approach
Dario Di Palma
Giovanni Maria Biancofiore
Vito Walter Anelli
Fedelucio Narducci
Tommaso Di Noia
E. Sciascio
ALM
299
38
0
07 Sep 2023
How Expressive are Graph Neural Networks in Recommendation?
How Expressive are Graph Neural Networks in Recommendation?International Conference on Information and Knowledge Management (CIKM), 2023
Xuheng Cai
Lianghao Xia
Xubin Ren
Chao Huang
275
7
0
22 Aug 2023
Impression-Aware Recommender Systems
Impression-Aware Recommender Systems
F. B. P. Maurera
Maurizio Ferrari Dacrema
P. Castells
Paolo Cremonesi
AI4TS
172
4
0
15 Aug 2023
Benchmarking Adaptative Variational Quantum Algorithms on QUBO Instances
Benchmarking Adaptative Variational Quantum Algorithms on QUBO InstancesInternational Conference on Quantum Computing and Engineering (QCE), 2023
Gloria Turati
Maurizio Ferrari Dacrema
Paolo Cremonesi
158
6
0
03 Aug 2023
A Survey on Popularity Bias in Recommender Systems
A Survey on Popularity Bias in Recommender Systems
Anastasiia Klimashevskaia
Dietmar Jannach
Mehdi Elahi
C. Trattner
605
87
0
02 Aug 2023
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and
  Reproducibility-driven Analysis
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven AnalysisACM Conference on Recommender Systems (RecSys), 2023
Vito Walter Anelli
Daniele Malitesta
Claudio Pomo
Alejandro Bellogín
Tommaso Di Noia
E. Sciascio
265
17
0
01 Aug 2023
On (Normalised) Discounted Cumulative Gain as an Off-Policy Evaluation
  Metric for Top-$n$ Recommendation
On (Normalised) Discounted Cumulative Gain as an Off-Policy Evaluation Metric for Top-nnn RecommendationKnowledge Discovery and Data Mining (KDD), 2023
Olivier Jeunen
Ivan Potapov
Aleksei Ustimenko
ELMOffRL
341
20
0
27 Jul 2023
Understanding User Behavior in Carousel Recommendation Systems for Click
  Modeling and Learning to Rank
Understanding User Behavior in Carousel Recommendation Systems for Click Modeling and Learning to RankWeb Search and Data Mining (WSDM), 2023
Santiago de Leon-Martinez
CMLLRM
130
4
0
04 Jul 2023
Of Spiky SVDs and Music Recommendation
Of Spiky SVDs and Music RecommendationACM Conference on Recommender Systems (RecSys), 2023
Darius Afchar
Romain Hennequin
Vincent Guigue
180
5
0
30 Jun 2023
RecFusion: A Binomial Diffusion Process for 1D Data for Recommendation
RecFusion: A Binomial Diffusion Process for 1D Data for Recommendation
Gabriel Bénédict
Olivier Jeunen
Samuele Papa
Samarth Bhargav
Daan Odijk
Maarten de Rijke
DiffM
240
12
0
15 Jun 2023
It's Enough: Relaxing Diagonal Constraints in Linear Autoencoders for
  Recommendation
It's Enough: Relaxing Diagonal Constraints in Linear Autoencoders for RecommendationAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023
Jaewan Moon
Hye-young Kim
Jongwuk Lee
218
8
0
22 May 2023
Eye Tracking as a Source of Implicit Feedback in Recommender Systems: A
  Preliminary Analysis
Eye Tracking as a Source of Implicit Feedback in Recommender Systems: A Preliminary AnalysisEye Tracking Research & Application (ETRA), 2023
Santiago de Leon-Martinez
Robert Moro
Maria Bielikova
77
3
0
12 May 2023
Survey of Federated Learning Models for Spatial-Temporal Mobility
  Applications
Survey of Federated Learning Models for Spatial-Temporal Mobility Applications
Yacine Belal
Sonia Ben Mokhtar
Hamed Haddadi
Jaron Wang
A. Mashhadi
FedML
309
18
0
09 May 2023
When Newer is Not Better: Does Deep Learning Really Benefit
  Recommendation From Implicit Feedback?
When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback?Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023
Yushun Dong
Jundong Li
Tobias Schnabel
225
12
0
02 May 2023
Recommender Systems: A Primer
Recommender Systems: A Primer
P. Castells
Dietmar Jannach
OffRL
147
9
0
06 Feb 2023
Job recommendations: benchmarking of collaborative filtering methods for
  classifieds
Job recommendations: benchmarking of collaborative filtering methods for classifieds
Robert Kwieciñski
A. Filipowska
Tomasz Górecki
V. Dubrov
167
10
0
19 Jan 2023
Tensor-based Sequential Learning via Hankel Matrix Representation for
  Next Item Recommendations
Tensor-based Sequential Learning via Hankel Matrix Representation for Next Item RecommendationsIEEE Access (IEEE Access), 2022
Evgeny Frolov
Ivan Oseledets
140
8
0
12 Dec 2022
Towards Reliable Item Sampling for Recommendation Evaluation
Towards Reliable Item Sampling for Recommendation EvaluationAAAI Conference on Artificial Intelligence (AAAI), 2022
Dong Li
Ruoming Jin
Zhenming Liu
Bin Ren
Jing Gao
Zhi Liu
138
10
0
28 Nov 2022
Hyperparameter optimization in deep multi-target prediction
Hyperparameter optimization in deep multi-target prediction
Dimitrios Iliadis
Marcel Wever
B. De Baets
Willem Waegeman
130
1
0
08 Nov 2022
Time-aware Self-Attention Meets Logic Reasoning in Recommender Systems
Time-aware Self-Attention Meets Logic Reasoning in Recommender SystemsIEEE International Joint Conference on Neural Network (IJCNN), 2022
Zhijian Luo
Zihan Huang
Jiahui Tang
Yueen Hou
Yanzeng Gao
LRM
181
1
0
29 Aug 2022
On the Generalizability and Predictability of Recommender Systems
On the Generalizability and Predictability of Recommender SystemsNeural Information Processing Systems (NeurIPS), 2022
Duncan C. McElfresh
Sujay Khandagale
Jonathan Valverde
John P. Dickerson
Colin White
183
11
0
23 Jun 2022
Synthetic Data-Based Simulators for Recommender Systems: A Survey
Synthetic Data-Based Simulators for Recommender Systems: A Survey
Elizaveta Stavinova
A. Grigorievskiy
A. Volodkevich
P. Chunaev
Klavdiya Olegovna Bochenina
D. Bugaychenko
SyDa
147
9
0
22 Jun 2022
Preference Dynamics Under Personalized Recommendations
Preference Dynamics Under Personalized RecommendationsACM Conference on Economics and Computation (EC), 2022
Sarah Dean
Jamie Morgenstern
199
40
0
25 May 2022
A Review on Pushing the Limits of Baseline Recommendation Systems with
  the integration of Opinion Mining & Information Retrieval Techniques
A Review on Pushing the Limits of Baseline Recommendation Systems with the integration of Opinion Mining & Information Retrieval Techniques
D. Piyadigama
Guhanathan Poravi
VLM
85
0
0
03 May 2022
Sources of Irreproducibility in Machine Learning: A Review
Sources of Irreproducibility in Machine Learning: A Review
Odd Erik Gundersen
Kevin Coakley
Christine R. Kirkpatrick
Yolanda Gil
SyDa
254
44
0
15 Apr 2022
Recommendation as Language Processing (RLP): A Unified Pretrain,
  Personalized Prompt & Predict Paradigm (P5)
Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)ACM Conference on Recommender Systems (RecSys), 2022
Shijie Geng
Shuchang Liu
Zuohui Fu
Yingqiang Ge
Zelong Li
VLMAI4TS
621
652
0
24 Mar 2022
Towards Reproducible Network Traffic Analysis
Towards Reproducible Network Traffic Analysis
Jordan Holland
Paul Schmitt
Prateek Mittal
Nick Feamster
117
8
0
23 Mar 2022
The worst of both worlds: A comparative analysis of errors in learning
  from data in psychology and machine learning
The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learningAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2022
Jessica Hullman
Sayash Kapoor
Priyanka Nanayakkara
Andrew Gelman
Arvind Narayanan
435
42
0
12 Mar 2022
GAN-based Matrix Factorization for Recommender Systems
GAN-based Matrix Factorization for Recommender SystemsACM Symposium on Applied Computing (SAC), 2022
Ervin Dervishaj
Paolo Cremonesi
110
20
0
20 Jan 2022
An Evaluation Study of Generative Adversarial Networks for Collaborative
  Filtering
An Evaluation Study of Generative Adversarial Networks for Collaborative FilteringEuropean Conference on Information Retrieval (ECIR), 2022
F. B. P. Maurera
Maurizio Ferrari Dacrema
Paolo Cremonesi
211
2
0
05 Jan 2022
Revisiting the Performance of iALS on Item Recommendation Benchmarks
Revisiting the Performance of iALS on Item Recommendation Benchmarks
Steffen Rendle
Walid Krichene
Li Zhang
Y. Koren
147
70
0
26 Oct 2021
Feature Selection for Recommender Systems with Quantum Computing
Feature Selection for Recommender Systems with Quantum Computing
Riccardo Nembrini
Maurizio Ferrari Dacrema
Paolo Cremonesi
149
54
0
11 Oct 2021
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